Planny

planny

Welcome to another announcement of the Startups of the Year 2023. This announcement covers all the special categories of Startups of the Year. This year, almost 30,000 startups across the globe were nominated, with over 600,000 votes cast in the running for Startup of the Year, surpassing the last award’s votes by almost 3x! Let’s see who won! Remote, Earth With 208 votes, wins the Startups of the Year, Remote, Earth! CIC Chain US Misc In  US Misc , is the winner with 1193 votes. Reship Colony Nevis Misc The startup of the year in Nevis Misc is . Spool Canada Misc The startup of the year in Canada Misc is . My Website is Online Mexico Misc The startup of the year in Mexico Misc is . Cion Digital UK, Misc , a 3D interactive parts catalog and work instructions SaaS platform software for OEM’s, wins! Partful Germany Misc Developing services to connect people all around the world tomorrowSpace Italy Misc comes out as the winner in with 37 votes! Planny Italy Greece Misc , in the cloud computing, AI, and data industry wins! The Signal Group Spain Misc is the winner in with 52 votes! Vertiports Network Spain Finland Misc wins in with 101 votes! Ikius Finland Russia Misc The Startup of the Year in is with 22 votes! Russia RentProg Georgia Misc is the winner in ! Constant Cash Offer Georgia Sweden Misc earns 209 votes to become the Startup of the Year in ! Intergiro Sweden Romania Misc The winner in is ! Romania ReactiveDoc Czech Republic Misc wins in the ! ISIA Czech Republic Lithuania Misc The winner in is ! Lithuania SearchNode Estonia Misc The winner in is ! Estonia Nerian Network Norway Misc wins in ! Utleieappen Norway Poland Misc is the winner in ! Zencal Poland Portugal Misc The winner in is ! Portugal Accelerator App Ukraine Misc The winner in is the ! Ukraine Crypto Cossacks Club Iceland Misc wins in with 89 votes! JSON2Video Iceland Hungary Misc wins in ! SURVIOT Hungary Ireland Misc In , the Startup of the Year is ! Ireland Payzaar Guernsey Misc The Startup of the Year in is ! Guernsey Infinite Canvas Malta Misc With 86 points, becomes the Startup of the Year in ! Metaverse Architects Malta Slovenia Misc is the Startup of the Year in ! d.labs Slovenia Luxembourg Misc With 57 votes, takes home the cake in ! Greenworlder Luxembourg Bulgaria Misc wins in ! iBlueMenú Bulgaria Macedonia Misc earns 88 votes to become the Startup of the Year in ! PlaceWar Macedonia Monaco Misc is the winner in ! InnoDeep Monaco Switzerland Misc in the MarketingTech Industry wins! LinkDrip Bosnia And Herzegovina Misc is the winner in ! Robinize Bosnia And Herzegovina Belgium Misc , a global network and marketplace for requesting and providing specified, fresh content on demand, wins! Aviark France Misc , an agriculture software and analytics company dedicated to helping farmers produce more and better, wins! Perfarmer Austria Misc , an open-source password manager specifically designed for enterprises, wins! Vaulteron Turkey Misc in the Content Management System (CMS) Industry wins! Contentrain Australia Misc claims the victory with 111 votes! 👑 IMPAKT IT New Zeland Misc Odd Jobs claims victory with 11 votes! Singapore Misc The startup of the year in Singapore Misc is with 62 votes. Neliti Palestine Misc The startup of the year in Palestine Misc is . 3amal Malaysia Misc. The startup of the year in Malaysia Misc is . Oyen Pet Insurance Bahrain Misc The startup of the year in Bahrain Misc is . Bookr Pakistan Misc The startup of the year in Pakistan Misc is . Azal Kazakhstan Misc The startup of the year in Kazakhstan Misc is . Kazakhmys.academy Azerbaijan Misc The startup of the year in Azerbaijan Misc is . Menti Vietnam Misc The startup of the year in Vietnam Misc is . RaceFi Saudi Arabia Misc The startup of the year in Saudi Arabia Misc is . Shera Tokens Philippines Misc The startup of the year in Philippines Misc is . edamama Bangladesh Misc The startup of the year in Bangladesh Misc is . FormBold Thailand Misc The startup of the year in Thailand Misc is . HappyLand Israel Misc The startup of the year in Israel Misc is . Otterize United Arab Emirates Misc The startup of the year in UAE Misc is . The Scalable CFO India Misc The startup of the year in India Misc is . 5ire China Misc The startup of the year in China Misc is . Fairyland Indonesia Misc The startup of the year in Indonesia Misc is . Dijital Generasi Kreasi Nepal Misc The startup of the year in Nepal Misc is . StackMyStore South Korea Misc The startup of the year in South Korea Misc is . OLIVE Sri Lanka Misc The startup of the year in Sri Lanka Misc is . clovatel Hotel Suite of solution Japan Misc The startup of the year in Japan Misc is . Response insight Uganda Misc ENVENTURE is king of the hill!🎉 Anguilla Misc Kubiya is the Startup of the Year with 45 votes!🎉 Burkina Faso Misc It’s a win for GVente!🎉 Tunisia Misc No one did it like True Delta!🎉 Algeria Misc Workflow Dashboard wins!🎉 Mauritius Misc Cube Consumer Services takes home the cake.🎉 Namibia Misc 174 votes, and Billet steals the show.🎉 Ghana Misc SMS NOTIFY GHANA takes it with 41 votes!🎉 Morocco Misc After 16 votes, SafeExchange is the Startup of the Year.🎉 Kenya Misc RueSuites wins!🎉 Botswana Misc Procurement Institute App comes out on top with highest number of votes!🎉 South Africa Misc SHIFT wins it all with the highest number of votes!🎉 Egypt Misc Alva emerges as Startup of the Year.🎉 Tanzania Misc JUPITER looms largest with highest number of votes!🎉 Republic Of Congo Misc Julizha is the Startup of the Year!🎉 Ethiopia Misc BEATCARES came out on top!🎉 Mauritania Misc The Startup of the Year is 3meel 🎉 Nigeria Misc With top votes, BoomKit takes home the goods.🎉 BoomKit is in the Music Tech Industry. Rwanda Misc TodoBoard is Startup of the Year!🎉 TodoBoard is in the Enterprise Collaboration Industry Brazil Misc The winner in is with 48 votes! Brazil SleekFlow Chile Misc is the Startup of the Year in ! ApiChat Chile Panama Misc is the Startup of the Year in ! PurpUX Panama Argentina Misc is the winner in with 27 votes! Rubicom Argentina Venezuela Misc In , the winner is ! Venezuela conectApp Colombia Misc The winner in is ! Colombia Violet Cundinamarca, Colombia The Startup of the Year in is ! Cundinamarca Voy Yo Ecuador Misc is the winner in ! SaaS for Trustees Ecuador British Virgin Islands Misc has won with the highest number of votes! GoMining Cayman Islands Misc has won the contest with highest number of votes! Dtravel Cyprus - Europe has won the Startups of the Year from Cyprus! Latenode Puerto Rico Misc takes the winning crown! Immutable Holdings San Juan, Puerto Rico is the Startups of the year! XRCasino Grand Cayman, Cayman Islands wins the Startups of the Year! Berachain Congratulations y’all. We will contact you with details on your winnings! See the global and other regional announcements . here About HackerNoon’s Startups Of The Year Startups of The Year is HackerNoon’s Flagship community-driven event celebrating startups that survived and thrived in 2023. 30,000 startups across 4200+ cities and six continents participated in 2023 to be crowned the best startup in their city. Visit our page to learn more. FAQ Companies that blog more get 67% more leads - Jumpstart your company’s blogging journey by purchasing our . Business Blogging Package The 2023 Startups Of The Year is sponsored by: . . The winners will get a free .Tech Domain, a HackerNoon NFT, and a Tech Company News Page. TECH Domains

Startups of the Year 2023: Remote/Misc Winners

The New York Times Company v. Microsoft Corporation Court Filing December 27, 2023 is part of . You can jump to any part in this filing . This is part 6 of 27. HackerNoon’s Legal PDF Series here IV. FACTUAL ALLEGATIONS A. The New York Times and its Mission 3. A Commitment to Quality Journalism 38. It takes enormous resources to publish, on average, more than 250 original articles every day. Many of these articles take months—and sometimes longer—to report. That output is the work of approximately 5,800 full-time equivalent Times employees(as of December 31, 2022), some 2,600 of whom are directly involved in The Times’s journalism operations. 39. Quite often, the most vital news reporting for society is the most resource-intensive. Some of The Times’s most important journalism requires deploying teams of journalists at great cost to report on the ground around the world, providing best-in-class security and support, filing lawsuits against government entities to bring information to light, and supporting journalists through investigations that can take months or years. 40. Subscription, advertising, licensing, and affiliate revenue make this reporting possible. In 1996, The Times launched a core news website, alongside its paid print edition, that was free. As readers shifted from print news to digital products, The Times—like most print publishers—faced the prospect of not being able to continue funding its journalism. In response, The Times reinvented its business model to incorporate digital subscriptions. The Times launched its metered paywall in 2011, in what it called “a bet that readers will pay for news they are accustomed to getting free.”[2] 41. Thanks to the quality of The Times’s journalism, that strategic innovation paid off, which allowed The Times to continue to exist and to thrive. Today, the vast majority of subscribers are digital-only. In the 12 years since The Times launched its paywall, it has grown its paid digital subscribership and developed a direct relationship with its online audience through its tireless commitment to making journalism “worth paying for.” Generating and maintaining direct traffic to its online content and mobile applications are critical components of The Times’s financial success. 42. By the third quarter of 2023, The Times had nearly 10.1 million digital and print subscribers worldwide. The Times aims to have 15 million subscribers by year-end 2027. 43. The Times makes journalism “worth paying for” by publishing articles that are exhaustively researched and reported, thoughtfully written, carefully edited, and thoroughly factchecked. 44. In addition, The Times has deepened its relationship with its readers by expanding its offerings to better encompass its readers’ specific interests, including best-in-class offerings like Cooking, Wirecutter, Games, and The Athletic. 45. The Times’s paywall does not require payment for all access to The Times’s content. To build audience engagement and loyalty, The Times’s access model generally offers registered users free access to a limited number of articles and other content before requiring them to subscribe for access to additional content. Approximately 50 to 100 million users, on average, engage with The Times’s digital content each week. This traffic is a key source of advertising revenue and helps drive future subscriptions to The Times. 46. The Times also compiled digital archives of all its material going back to its founding, at significant cost. Its digital archives include The New York Times Article Archive, with partial and full-text digital versions of articles from 1851 to today, and the TimesMachine, a browser-based digital replica of all issues from 1851 to 2002. This represents a singular database of contemporaneous language and information, as well as a unique and valuable historical record. The Times also provides its own API that allows researchers and academics to search Times content for non-commercial purposes. Continue Reading . Here [2] Jeremy W. Peters, The Times Announces Digital Subscription Plan, N.Y. TIMES (Mar. 17, 2011), https://www.nytimes.com/2011/03/18/business/media/18times.html. About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case 1:23-cv-11195 retrieved on December 29, 2023, from is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. nycto-assets.nytimes.com

The Times v. Microsoft/OpenAI: A Commitment to Quality Journalism (6)

টাইমস বনাম মাইক্রোসফ্ট/ওপেনএআই: মানসম্পন্ন সাংবাদিকতার প্রতি অঙ্গীকার (6)

The Times vs. Microsoft/OpenAI: Ein Bekenntnis zum Qualitätsjournalismus (6)

The Times contra Microsoft/OpenAI: un compromiso con el periodismo de calidad (6)

The Times contre Microsoft/OpenAI : un engagement pour un journalisme de qualité (6)

द टाइम्स बनाम माइक्रोसॉफ्ट/ओपनएआई: गुणवत्तापूर्ण पत्रकारिता के प्रति प्रतिबद्धता (6)

タイムズ対マイクロソフト/OpenAI: 質の高いジャーナリズムへの取り組み (6)

The Times 대 Microsoft/OpenAI: 고품질 저널리즘에 대한 약속(6)

The Times x Microsoft/OpenAI: um compromisso com o jornalismo de qualidade (6)

The Times против Microsoft/OpenAI: приверженность качественной журналистике (6)

The Times - Microsoft/OpenAI: Kaliteli Gazeteciliğe Bağlılık (6)

The Times v. Microsoft/OpenAI: Cam kết về chất lượng báo chí (6)

《泰晤士报》诉 Microsoft/OpenAI：对高质量新闻的承诺 (6)

MAHE, Seychelles, December 9th, 2024/Chainwire/--iYield provides users with a free and secure platform for tracking cryptocurrency cryptocurrency, DeFi, and traditional finances. iYield was founded by Gentleman James, a crypto native and experienced DeFi investor. Driven by his need for a better way to manage and track his crypto, including DeFi yields, and frustrated by juggling spreadsheets and multiple dashboards, James built iYield for investors like himself. Unlike portfolio trackers that only display asset values, iYield reveals a full financial picture by also supporting debts, incomes, and expenses – in both crypto and fiat. iYield’s dashboard lets users compare returns from their DeFi positions side by side, eliminating uncertainty and offering them the clarity needed to make smarter, more informed decisions. Simplified Financial Management iYield has integrated over 16,000 tokens across 17 blockchains, 40 top DeFi, and staking protocols, along with all fiat currencies, into one unified platform. This gives users real-time insights into their finances empowering them to manage everything from one secure dashboard. iYield enables users to track a broad range of assets, from Bitcoin and Eigenlayer restaking to Solana-based tokens, traditional savings accounts, and daily expenses. The platform includes tools for budgeting, financial forecasting, and cash flow monitoring, helping users enhance their financial management and plan for long-term growth. https://www.youtube.com/embed/hO1HMzON1AY https://youtu.be/hO1HMzON1AY Real-Time DeFi Yield Tracking iYield distinguishes itself among other crypto portfolio trackers by integrating with a growing list of the top DeFi and StakeFi protocols, including Aave, Ethena, Ether.fi, Eigenlayer, Pendle, Rocket Pool, Thorchain, Uniswap, and Zircuit. The platform also provides real-time tracking of investments, staking rewards, and income streams. New Feature: Historical Value Tracking iYield's latest feature enhances financial tracking by introducing the ability to view historical values. Users can now access detailed records of their items' value and balance from the moment they were added to the platform. This feature enables a deeper analysis of financial decisions, helping users understand their impact and refine strategies for long-term success. Built on Privacy and Security iYield is built on a privacy-first foundation, ensuring that users can plan and manage their finances without ever compromising their personal data. This starts with anonymity. Unlike many other platforms, iYield does not collect user IDs or sell user data, and it never asks for access to funds or personal information. The platform operates without ads, data mining, or fees, ensuring a private and secure experience for all users. About iYield iYield’s mission is to empower individuals to take full control of their financial future. With a clear, holistic view of both crypto and fiat finances, users can confidently make informed decisions about their long-term financial growth. From budgeting and cash flow to comparing DeFi yields side by side, iYield equips users with the tools they need to make better decisions and gain financial independence, all for free. For more information, users can visit iYield’s Website | Twitter | Discord Contact Marketing Director Josh iYield josh@iyield.com This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here MAHE, Seychelles, December 9th, 2024/Chainwire/--iYield provides users with a free and secure platform for tracking cryptocurrency cryptocurrency, DeFi, and traditional finances. iYield was founded by Gentleman James, a crypto native and experienced DeFi investor. Driven by his need for a better way to manage and track his crypto, including DeFi yields, and frustrated by juggling spreadsheets and multiple dashboards, James built iYield for investors like himself. Unlike portfolio trackers that only display asset values, iYield reveals a full financial picture by also supporting debts, incomes, and expenses – in both crypto and fiat. iYield’s dashboard lets users compare returns from their DeFi positions side by side, eliminating uncertainty and offering them the clarity needed to make smarter, more informed decisions. Simplified Financial Management iYield has integrated over 16,000 tokens across 17 blockchains, 40 top DeFi, and staking protocols, along with all fiat currencies, into one unified platform. This gives users real-time insights into their finances empowering them to manage everything from one secure dashboard. iYield enables users to track a broad range of assets, from Bitcoin and Eigenlayer restaking to Solana-based tokens, traditional savings accounts, and daily expenses. The platform includes tools for budgeting, financial forecasting, and cash flow monitoring, helping users enhance their financial management and plan for long-term growth. https://www.youtube.com/embed/hO1HMzON1AY https://www.youtube.com/embed/hO1HMzON1AY https://www.youtube.com/embed/hO1HMzON1AY https://youtu.be/hO1HMzON1AY https://youtu.be/hO1HMzON1AY https://youtu.be/hO1HMzON1AY Real-Time DeFi Yield Tracking iYield distinguishes itself among other crypto portfolio trackers by integrating with a growing list of the top DeFi and StakeFi protocols, including Aave, Ethena, Ether.fi, Eigenlayer, Pendle, Rocket Pool, Thorchain, Uniswap, and Zircuit. The platform also provides real-time tracking of investments, staking rewards, and income streams. New Feature: Historical Value Tracking iYield's latest feature enhances financial tracking by introducing the ability to view historical values. Users can now access detailed records of their items' value and balance from the moment they were added to the platform. This feature enables a deeper analysis of financial decisions, helping users understand their impact and refine strategies for long-term success. Built on Privacy and Security iYield is built on a privacy-first foundation, ensuring that users can plan and manage their finances without ever compromising their personal data. This starts with anonymity. Unlike many other platforms, iYield does not collect user IDs or sell user data, and it never asks for access to funds or personal information. The platform operates without ads, data mining, or fees, ensuring a private and secure experience for all users. About iYield iYield’s mission is to empower individuals to take full control of their financial future. With a clear, holistic view of both crypto and fiat finances, users can confidently make informed decisions about their long-term financial growth. iYield’s iYield’s From budgeting and cash flow to comparing DeFi yields side by side, iYield equips users with the tools they need to make better decisions and gain financial independence, all for free. For more information, users can visit iYield’s Website | Twitter | Discord Website Website Twitter Twitter Discord Discord Contact Marketing Director Josh iYield josh@iyield.com This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here here here

iYield Launches Crypto's 1st Financial Planning Tool

iYield ukax Crypto ukan 1r Qullqituqit amtäwip uñt’ayi

iYield lanza la primera herramienta de planificación financiera para criptomonedas

iYield-ek Crypto-ren 1. finantza-plangintza tresna abiarazten du

iYield lanseeraa Crypton ensimmäisen taloussuunnittelutyökalun

iYield、暗号通貨初の金融計画ツールをリリース

iYield izlaiž Crypto 1. finanšu plānošanas rīku

iYield lanceert eerste financiële planningstool voor crypto

iYield wprowadza pierwsze narzędzie do planowania finansowego w Crypto

iYield Crypto 1 kaq Qullqimanta Planificación Herramienta qallarichin

iYield запускает первый инструмент финансового планирования Crypto

Inilunsad ng iYield ang 1st Financial Planning Tool ng Crypto

iYield 推出加密货币的首个财务规划工具

Is Staying Organized the Key to Your Success? Definitely. How can you keep track of your new projects and opportunities if you stay messy? I recommend becoming a bit of a freak when it comes to systematically writing things down. You won’t miss any deadlines or waste time on searching for crucial info. For me, tracking my online activity and newly acquired contacts was a real game changer. I became more consistent and engaged. Since I didn’t want to jump from one place to another, I did it all using one tool - Notion. So, What Is Notion, and Why Even Bother Using It? I came across Notion a few years ago while looking for an online tool to gather all my university materials. Quickly, it became my main professional tool for keeping track of all current tasks, deadlines, contacts, and ideas. How I did organize my space there? I divided my menu bar into 4 main areas: Tasks - a board with all planned, in progress, requiring review and done tasks. It is the basis for my daily to-do lists.


Content planner - used to track my online activity on all social media platforms and plan future publications.


People - an organized contact list of people within my network, including the topics of most recent communication with them.


Ideas - a creative space gathering all my professional ideas that don’t have a structured vision yet (and aren’t therefore tasks). In this article, I’ll focus on two areas (‘Content planner’ and ‘People’) that really improved the way my network has grown and become more structured. How to Track Your Social Media Activity Using Notion? In the ‘Content Planner’ area, I create a table with specific columns: Date of publication


Type of the post - I divide them into text, graphic, share, and engage (for example, for the polls or open-ended questions)


Title of the post and its content (on a separate page)


Status: not started, in progress, ready to publish, and done


Person: just in case it’s not me who will be publishing the content


Platform: here, I tag the social media platform on which the publication will appear Keeping track of my publications helps me review my progress and see how the number of posts affects my following and engagement on certain channels. Additionally, I don’t have to scroll through my feed to check if I mentioned the same topics recently; I do it more quickly - by using the table. Finally, even though I can schedule posts on certain platforms, I sometimes come across time or character limitations. Here, I can plan my content ahead, still insert some changes on the way, and then just schedule publications directly on the platforms weekly. Alternatively, I can set an alarm and upload them on the exact day of publication. How to Manage Your Network Contacts With Notion? LinkedIn is no doubt the most popular platform for professional communication and network growth. Still, I sometimes contact people through mail or other channels. Again, not to waste time wondering who, where, and regarding what I last contacted, I keep all that info written down and organized. In the ‘People area,’ I also create a table and name certain columns: Name


Type - for me, it’s mostly journalists, podcast people, or entrepreneurs.


Last update - the topic of our last conversation.


Status - a special formula (easily found in the settings) tells me if it’s time to get in touch with someone once again.


Contact info - a mail or a pasted link to a LinkedIn account. This way, I have all crucial and practical information stored in a clear system. I save time I would have spent on scrolling through chat messages or mail by keeping all information in one place. And most importantly, I manage to engage with various people consistently. In Short Become more organized, more effective, and value your own time. Use Notion to track your social media activity and monitor your network! Thanks for reading ProductiveImpact! Click subscribe on the left to receive new posts and support my work. Check out my newsletter. And other socials: @productiveimpct Is Staying Organized the Key to Your Success? Definitely. How can you keep track of your new projects and opportunities if you stay messy? I recommend becoming a bit of a freak when it comes to systematically writing things down. You won’t miss any deadlines or waste time on searching for crucial info. For me, tracking my online activity and newly acquired contacts was a real game changer. I became more consistent and engaged. Since I didn’t want to jump from one place to another, I did it all using one tool - Notion. So, What Is Notion, and Why Even Bother Using It? I came across Notion a few years ago while looking for an online tool to gather all my university materials. Quickly, it became my main professional tool for keeping track of all current tasks, deadlines, contacts, and ideas. How I did organize my space there? I divided my menu bar into 4 main areas: Tasks - a board with all planned, in progress, requiring review and done tasks. It is the basis for my daily to-do lists. Content planner - used to track my online activity on all social media platforms and plan future publications. People - an organized contact list of people within my network, including the topics of most recent communication with them. Ideas - a creative space gathering all my professional ideas that don’t have a structured vision yet (and aren’t therefore tasks). Tasks - a board with all planned, in progress, requiring review and done tasks. It is the basis for my daily to-do lists. Tasks - a board with all planned, in progress, requiring review and done tasks. It is the basis for my daily to-do lists. Tasks planned, in progress, review done Content planner - used to track my online activity on all social media platforms and plan future publications. Content planner - used to track my online activity on all social media platforms and plan future publications. Content planner People - an organized contact list of people within my network, including the topics of most recent communication with them. People - an organized contact list of people within my network, including the topics of most recent communication with them. People Ideas - a creative space gathering all my professional ideas that don’t have a structured vision yet (and aren’t therefore tasks). Ideas - a creative space gathering all my professional ideas that don’t have a structured vision yet (and aren’t therefore tasks). Ideas In this article, I’ll focus on two areas (‘Content planner’ and ‘People’) that really improved the way my network has grown and become more structured. How to Track Your Social Media Activity Using Notion? In the ‘Content Planner’ area, I create a table with specific columns: Date of publication Type of the post - I divide them into text, graphic, share, and engage (for example, for the polls or open-ended questions) Title of the post and its content (on a separate page) Status: not started, in progress, ready to publish, and done Person: just in case it’s not me who will be publishing the content Platform: here, I tag the social media platform on which the publication will appear Date of publication Date of publication Date of publication Type of the post - I divide them into text, graphic, share, and engage (for example, for the polls or open-ended questions) Type of the post - I divide them into text, graphic , share , and engage (for example, for the polls or open-ended questions) Type of the post text, graphic share engage Title of the post and its content (on a separate page) Title of the post and its content (on a separate page) Title of the post and its content Status: not started, in progress, ready to publish, and done Status : not started , in progress , ready to publish, and done Status not started in progress ready to publish, done Person: just in case it’s not me who will be publishing the content Person : just in case it’s not me who will be publishing the content Person Platform: here, I tag the social media platform on which the publication will appear Platform : here, I tag the social media platform on which the publication will appear Platform Keeping track of my publications helps me review my progress and see how the number of posts affects my following and engagement on certain channels. Additionally, I don’t have to scroll through my feed to check if I mentioned the same topics recently; I do it more quickly - by using the table. Finally, even though I can schedule posts on certain platforms, I sometimes come across time or character limitations. Here, I can plan my content ahead, still insert some changes on the way, and then just schedule publications directly on the platforms weekly. Alternatively, I can set an alarm and upload them on the exact day of publication. How to Manage Your Network Contacts With Notion? LinkedIn is no doubt the most popular platform for professional communication and network growth. Still, I sometimes contact people through mail or other channels. Again, not to waste time wondering who, where, and regarding what I last contacted, I keep all that info written down and organized. In the ‘People area,’ I also create a table and name certain columns: Name Type - for me, it’s mostly journalists, podcast people, or entrepreneurs. Last update - the topic of our last conversation. Status - a special formula (easily found in the settings) tells me if it’s time to get in touch with someone once again. Contact info - a mail or a pasted link to a LinkedIn account. Name Name Name Type - for me, it’s mostly journalists, podcast people, or entrepreneurs. Type - for me, it’s mostly journalists, podcast people, or entrepreneurs. Type Last update - the topic of our last conversation. Last update - the topic of our last conversation. Last update Status - a special formula (easily found in the settings) tells me if it’s time to get in touch with someone once again. Status - a special formula (easily found in the settings) tells me if it’s time to get in touch with someone once again. Status Contact info - a mail or a pasted link to a LinkedIn account. Contact info - a mail or a pasted link to a LinkedIn account. Contact info This way, I have all crucial and practical information stored in a clear system. I save time I would have spent on scrolling through chat messages or mail by keeping all information in one place. And most importantly, I manage to engage with various people consistently. In Short Become more organized, more effective, and value your own time. Use Notion to track your social media activity and monitor your network! Thanks for reading ProductiveImpact! Click subscribe on the left to receive new posts and support my work. Check out my newsletter . newsletter And other socials: @productiveimpct @productiveimpct

How to Create a Content Planner and Contact List With Notion

We've all experienced the pressure of managing a flood of business requirements that need to be addressed in product releases. Whether it's critical features to meet regulatory demands, urgent client requests that impact productivity, or the development of a cutting-edge metric or dashboard pulling data from 11 odd tables that need to be fed into the database by applying complex transformation logic, the challenges are constant. Amidst the chaos and last-minute demands, how can a Product Manager effectively build and execute a release plan without constant disruptions? Well, here comes Time-Based and Scope-Based release planning which can soften the misery and help unwind and unclutter. Let’s Outline the Process by Building Through a Structure 1. Get all the User Functional and Non-Functional Requirements Documented Once the Business Requirements are received, follow the below pipeline: 1.1 Leverage your User Personas, and convert your Business Requirement into a user requirement. 1.2 Once User Requirements are created, assess them against your system requirements. 1.3 A System Requirement can further be broken down into a Function and Non-Functional Requirement. 1.4 Document your Functional Requirements into an integrated spreadsheet, as it will now become your master. Once the assessment is completed, break your requirements into ·       Functional and Non-Function Requirements (Indicative Classifications Below) As soon as this process is completed, 80% of the clarity on what you are supposed to build as a Product Manager will have been achieved. Outcome: Clearly documented Functional and Non Functional Requirements 2. Generate Time - Based Estimates for Each Functional Requirement As a Product Manager, we are secretly married to our Backlog; getting the right estimates to address the requirements in our Backlog is of utmost priority. Building a forecast and identifying predictability is loved by all, hence, one may start with initial high-level estimates based on estimation techniques such as: ·       T-Shirt Sizing ·       Relative Story Pointing And then, keep on refining these estimates as part of a continuous review. Outcome: High-Level Estimates on Functional Requirements 3. Start With Requirements Elicitation as Part of a Grooming Exercise Once your requirements are added, and High-Level estimates are achieved, proceed with a requirements elicitation exercise with your Functional and Tech SME’s to clearly understand the requirements in finer detail. This will help you as a Product Manager address finer technicalities and holistically assess the complexity of the feature development. Requirements Grooming exercise also helps mitigate scope risk, while enabling a streamlined release funnel which is understood by the team. Your Grooming Exercises are the first avenue where you will actually create User Stories, and combine the User Stories into features and EPICs. Outcome: User Stories and Requirement Breakdown into Product Features 4. Proceed With the Identification of Vertical and Horizontal Features Vertical Features - Features that are independent
Horizontal Features - Features dependent on Vertical Features completion A product will always have features that are statistically dependent and independent. Vertical features individually integrate into the Horizontal feature to build a fully scalable solution. For example, in an AI workflow product, your workflow (Horizontal feature) is dependent on individual integration of ‘workflow states’ (Vertical Features) which need to function efficiently. Thereafter, integrating with the holistic workflow to function as a single stream of functionality. Outcome: Clear Understanding on Dependent and Independent features, So, you know which ones to build first 5. Use a Value Stacking Framework and Develop Risk-Based Priority A Value Stacking Framework is an essential tool for Product Managers to objectively assess the relative value of different features. This approach involves systematically comparing features A, B, C, D, and so on, against a set of predefined criteria. These criteria might include regulatory impact, user impact, business alignment, technical feasibility, and/or market differentiation. Let’s Look at the Framework by an Example: ·  Feature A is assessed to have a Regulatory Impact ·  Feature B is assessed to have a Productivity Impact ·  Feature C is assessed to have a Market Differentiation Impact ·  Feature D is assessed to have a Critical Impact on other features (Vertical Feature) Based on your Use Case and Business driver, a Product Manager would be required to tailor the priority based on impact which is relevant to their need (Weighted Scoring). Hence, any feature having a Regulatory Impact should be paramount, followed by features that enable or enhance other functionalities. Productivity improvements come next, with market differentiation as the final consideration. Based on the above-weighted scoring, the ‘Relative Priority’ of features for release planning should be: The qualitative feature assessment framework helps eliminate bias, enables critical decision-making, and ensures that resources are allocated to features that offer the highest overall value to both users and the business. Outcome: Features identified based on relative value and risk. In Summary Having a clear direction for prioritization and a vetted framework that can be scaled to 90% of the problems can enable smoother release planning and help in stakeholder management. While, the plans are ever-changing and priorities evolve, providing clarity to team members and clients on the assessment of priority enables smoother and more frequent releases and minimizes surprises while enabling your product development at scale. We've all experienced the pressure of managing a flood of business requirements that need to be addressed in product releases. Whether it's critical features to meet regulatory demands, urgent client requests that impact productivity, or the development of a cutting-edge metric or dashboard pulling data from 11 odd tables that need to be fed into the database by applying complex transformation logic, the challenges are constant. Amidst the chaos and last-minute demands, how can a Product Manager effectively build and execute a release plan without constant disruptions? Well, here comes Time-Based and Scope-Based release planning which can soften the misery and help unwind and unclutter. Let’s Outline the Process by Building Through a Structure Let’s Outline the Process by Building Through a Structure 1. Get all the User Functional and Non-Functional Requirements Documented Once the Business Requirements are received, follow the below pipeline: 1.1 Leverage your User Personas, and convert your Business Requirement into a user requirement. 1.1 1.2 Once User Requirements are created, assess them against your system requirements. 1.2 1.3 A System Requirement can further be broken down into a Function and Non-Functional Requirement. 1.3 1.4 Document your Functional Requirements into an integrated spreadsheet, as it will now become your master. 1.4 Once the assessment is completed, break your requirements into ·       Functional and Non-Function Requirements (Indicative Classifications Below) (Indicative Classifications Below) As soon as this process is completed, 80% of the clarity on what you are supposed to build as a Product Manager will have been achieved. Outcome : Clearly documented Functional and Non Functional Requirements Outcome 2. Generate Time - Based Estimates for Each Functional Requirement Generate Time - Based Estimates for Each Functional Requirement As a Product Manager, we are secretly married to our Backlog; getting the right estimates to address the requirements in our Backlog is of utmost priority. Building a forecast and identifying predictability is loved by all, hence, one may start with initial high-level estimates based on estimation techniques such as: ·       T-Shirt Sizing ·       Relative Story Pointing And then, keep on refining these estimates as part of a continuous review. Outcome : High-Level Estimates on Functional Requirements Outcome 3. Start With Requirements Elicitation as Part of a Grooming Exercise 3. Start With Requirements Elicitation as Part of a Grooming Exercise Once your requirements are added, and High-Level estimates are achieved, proceed with a requirements elicitation exercise with your Functional and Tech SME’s to clearly understand the requirements in finer detail. This will help you as a Product Manager address finer technicalities and holistically assess the complexity of the feature development. Requirements Grooming exercise also helps mitigate scope risk, while enabling a streamlined release funnel which is understood by the team. Your Grooming Exercises are the first avenue where you will actually create User Stories, and combine the User Stories into features and EPICs. Outcome : User Stories and Requirement Breakdown into Product Features Outcome 4. Proceed With the Identification of Vertical and Horizontal Features 4. Proceed With the Identification of Vertical and Horizontal Features Vertical Features - Features that are independent Horizontal Features - Features dependent on Vertical Features completion Vertical Features - Features that are independent Vertical Features - Features that are independent Horizontal Features - Features dependent on Vertical Features completion Horizontal Features - Features dependent on Vertical Features completion A product will always have features that are statistically dependent and independent. Vertical features individually integrate into the Horizontal feature to build a fully scalable solution. For example, in an AI workflow product, your workflow (Horizontal feature) is dependent on individual integration of ‘workflow states’ (Vertical Features) which need to function efficiently. Thereafter, integrating with the holistic workflow to function as a single stream of functionality. Outcome : Clear Understanding on Dependent and Independent features, So, you know which ones to build first Outcome 5. Use a Value Stacking Framework and Develop Risk-Based Priority 5. Use a Value Stacking Framework and Develop Risk-Based Priority A Value Stacking Framework is an essential tool for Product Managers to objectively assess the relative value of different features. This approach involves systematically comparing features A, B, C, D, and so on, against a set of predefined criteria. These criteria might include regulatory impact, user impact, business alignment, technical feasibility, and/or market differentiation. Let’s Look at the Framework by an Example: Let’s Look at the Framework by an Example: ·  Feature A is assessed to have a Regulatory Impact ·  Feature B is assessed to have a Productivity Impact ·  Feature C is assessed to have a Market Differentiation Impact ·  Feature D is assessed to have a Critical Impact on other features (Vertical Feature) Based on your Use Case and Business driver, a Product Manager would be required to tailor the priority based on impact which is relevant to their need ( Weighted Scoring ). Weighted Scoring Hence, any feature having a Regulatory Impact should be paramount, followed by features that enable or enhance other functionalities. Productivity improvements come next, with market differentiation as the final consideration. Based on the above-weighted scoring, the ‘Relative Priority’ of features for release planning should be: The qualitative feature assessment framework helps eliminate bias, enables critical decision-making, and ensures that resources are allocated to features that offer the highest overall value to both users and the business. Outcome: Features identified based on relative value and risk. Outcome: In Summary In Summary Having a clear direction for prioritization and a vetted framework that can be scaled to 90% of the problems can enable smoother release planning and help in stakeholder management. While, the plans are ever-changing and priorities evolve, providing clarity to team members and clients on the assessment of priority enables smoother and more frequent releases and minimizes surprises while enabling your product development at scale.

How to Efficiently Perform Release Planning in Product Management

This is the second part of a series of articles on how GenAI is revolutionizing Rev-Ops functions in enterprise technology businesses. In the first part, we saw some broad applications of Gen AI in Rev Ops. In this article, we will explore how GenAI use cases are being developed and deployed in the first of the  four core Rev Ops pillars - business strategy and planning. A little bit about myself : I am a GTM veteran & Sr. Director of RevOps at Cisco. Business Planning - what is it, how is it done, and what is changing? Business Planning is the primary cross-functional performance in the corporate ballroom. Lead actors from Product, Engineering, Finance and Sales participate in this song-and-dance routine with Rev Ops called upon to choreograph the arrangement as tightly as possible. The perennial challenge in these situations is that everybody performs to their own sheets of music with not-so pleasant outcomes for the company or stakeholders. A single source of truth for business planning has historically been the holy grail of corp-strategy and execution if ever there was one. Enter language models with context awareness and generative capabilities. Generative AI enhances data-driven decision-making in business planning by providing advanced tools and capabilities that improve the efficiency, accuracy, and depth of insights. Here are some ways it contributes to this process: Democratising Data Accessibility and Usability: Generative AI makes data more understandable and accessible to people across different functions in an organization. Finally, we can move past domain specific jargons and inconsistent data structures by giving average user the ability to query and understand data in natural language. By combining this with intuitive interfaces and user-friendly data presentations, it democratizes data access and encourages a more inclusive approach to decision-making.


Real-Time Insights and Analysis: Generative AI can process vast amounts of structured and unstructured data quickly, providing executives with real-time, actionable insights. This capability allows businesses to identify trends and patterns that were previously invisible, enabling more informed decision-making.


Dynamic Scenario Planning and Modeling: Generative AI models can drastically lower the reaction times of business to emerging trends and geo-political situations, by allowing businesses to quickly simulate various scenarios and plan contingencies. This helps in testing different strategies and predicting outcomes without the need for extensive real-world experimentation.


Automation and Efficiency: While there has been a lot of discussion on AI replacing analysts and other workers, the more pertinent use case of AI in this space is in augmenting human capability. The automation of repetitive and time-consuming tasks through generative AI allows teams to focus on higher-value activities. This not only boosts operational efficiency but also supports a more agile business model that can quickly adapt to market changes. In the following articles, we will continue these discussions across Marketing, Sales, and Customer Success. This is the second part of a series of articles on how GenAI is revolutionizing Rev-Ops functions in enterprise technology businesses. In the first part , we saw some broad applications of Gen AI in Rev Ops. In this article, we will explore how GenAI use cases are being developed and deployed in the first of the  four core Rev Ops pillars - business strategy and planning. In the first part In the first part A little bit about myself : I am a GTM veteran & Sr. Director of RevOps at Cisco. Business Planning - what is it, how is it done, and what is changing? Business Planning - what is it, how is it done, and what is changing? Business Planning is the primary cross-functional performance in the corporate ballroom. Lead actors from Product, Engineering, Finance and Sales participate in this song-and-dance routine with Rev Ops called upon to choreograph the arrangement as tightly as possible. The perennial challenge in these situations is that everybody performs to their own sheets of music with not-so pleasant outcomes for the company or stakeholders. A single source of truth for business planning has historically been the holy grail of corp-strategy and execution if ever there was one. Enter language models with context awareness and generative capabilities. not-so pleasant outcomes for the company or stakeholders. not-so pleasant outcomes for the company or stakeholders. Generative AI enhances data-driven decision-making in business planning by providing advanced tools and capabilities that improve the efficiency, accuracy, and depth of insights. Here are some ways it contributes to this process: Democratising Data Accessibility and Usability: Generative AI makes data more understandable and accessible to people across different functions in an organization. Finally, we can move past domain specific jargons and inconsistent data structures by giving average user the ability to query and understand data in natural language. By combining this with intuitive interfaces and user-friendly data presentations, it democratizes data access and encourages a more inclusive approach to decision-making. Real-Time Insights and Analysis: Generative AI can process vast amounts of structured and unstructured data quickly, providing executives with real-time, actionable insights. This capability allows businesses to identify trends and patterns that were previously invisible, enabling more informed decision-making. Dynamic Scenario Planning and Modeling: Generative AI models can drastically lower the reaction times of business to emerging trends and geo-political situations, by allowing businesses to quickly simulate various scenarios and plan contingencies. This helps in testing different strategies and predicting outcomes without the need for extensive real-world experimentation. Automation and Efficiency: While there has been a lot of discussion on AI replacing analysts and other workers, the more pertinent use case of AI in this space is in augmenting human capability. The automation of repetitive and time-consuming tasks through generative AI allows teams to focus on higher-value activities. This not only boosts operational efficiency but also supports a more agile business model that can quickly adapt to market changes. Democratising Data Accessibility and Usability: Generative AI makes data more understandable and accessible to people across different functions in an organization. Finally, we can move past domain specific jargons and inconsistent data structures by giving average user the ability to query and understand data in natural language. By combining this with intuitive interfaces and user-friendly data presentations, it democratizes data access and encourages a more inclusive approach to decision-making. Democratising Data Accessibility and Usability: Generative AI makes data more understandable and accessible to people across different functions in an organization. Finally, we can move past domain specific jargons and inconsistent data structures by giving average user the ability to query and understand data in natural language . By combining this with intuitive interfaces and user-friendly data presentations, it democratizes data access and encourages a more inclusive approach to decision-making. average user the ability to query and understand data in natural language average user the ability to query and understand data in natural language Real-Time Insights and Analysis: Generative AI can process vast amounts of structured and unstructured data quickly, providing executives with real-time, actionable insights. This capability allows businesses to identify trends and patterns that were previously invisible, enabling more informed decision-making. Real-Time Insights and Analysis: Generative AI can process vast amounts of structured and unstructured data quickly, providing executives with real-time, actionable insights . This capability allows businesses to identify trends and patterns that were previously invisible, enabling more informed decision-making. real-time, actionable insights real-time, actionable insights Dynamic Scenario Planning and Modeling: Generative AI models can drastically lower the reaction times of business to emerging trends and geo-political situations, by allowing businesses to quickly simulate various scenarios and plan contingencies. This helps in testing different strategies and predicting outcomes without the need for extensive real-world experimentation. Dynamic Scenario Planning and Modeling : Generative AI models can drastically lower the reaction times of business to emerging trends and geo-political situations, by allowing businesses to quickly simulate various scenarios and plan contingencies. This helps in testing different strategies and predicting outcomes without the need for extensive real-world experimentation. Dynamic Scenario Planning and Modeling Dynamic Scenario Planning and Modeling Automation and Efficiency: While there has been a lot of discussion on AI replacing analysts and other workers, the more pertinent use case of AI in this space is in augmenting human capability. The automation of repetitive and time-consuming tasks through generative AI allows teams to focus on higher-value activities. This not only boosts operational efficiency but also supports a more agile business model that can quickly adapt to market changes. Automation and Efficiency: While there has been a lot of discussion on AI replacing analysts and other workers, the more pertinent use case of AI in this space is in augmenting human capability. The automation of repetitive and time-consuming tasks through generative AI allows teams to focus on higher-value activities. This not only boosts operational efficiency but also supports a more agile business model that can quickly adapt to market changes. In the following articles, we will continue these discussions across Marketing, Sales, and Customer Success.

Reimagining Rev-Ops with Gen AI: Always-On Strategy and Planning 

From product design to interior design and construction, design is a fundamental part of everything we touch and everywhere we go. However, the design process is incredibly involved and requires a high level of attention to detail — even one mistake could cause the entire design to come crashing down — which is why many designers are constantly looking for innovations that will make their jobs better, more efficient, and safer. What is Mixed Reality (MR)? One powerful new technology seems destined to shake up the design landscape for the better: mixed reality (MR). Although people might be familiar with the concepts of virtual reality (VR) and augmented reality (AR), MR takes this technology’s capabilities to a different level and will change the design process for the better. MR is made possible through a combination of the most powerful features of VR and AR technology. Where VR provides a fully immersive digital environment, AR overlays digital content onto the real world. MR allows users to interact and engage with 3D virtual objects using natural movements and gestures due to the technology’s ability to map out the user’s actual environment. The result is that users can see and manipulate digital elements as if they were truly present in the same physical space. Greg Sugar, President of LineZero, a strategic technology consultancy specializing in helping businesses adopt the latest technology to enhance employee experience and improve operational efficiency, has firsthand experience seeing the influence of MR and has helped several organizations adopt it. “MR technology allows those in the design process to visualize and analyze many aspects of their designs,” Sugar explains. “This can be incredibly helpful in the pre-construction stage, as it allows designers to envision their designs before they enter construction. This technology allows you to not only see everything you’re working on but also interact with it.” How MR will help businesses improve their design processes While mixed reality may appear to be just another passing tech trend or a fancy toy, it actually presents a multitude of advantages for both employees and businesses. From employee engagement to enabling increased precision and safety, MR can be a transformative force in businesses’ design processes. For example, since MR technology allows designers to visualize their design and build prototypes before building them in real life, designers’ vision can be better communicated, and any potential flaws in the design can be identified and rectified early on. MR gives users access to real-time data and visual aids, reducing the likelihood of human error in the design process. This helps with the final quality of the products being designed as well as their safety and reliability. In industries where a great deal of precision is required, MR can help ensure attention to detail from the early stages of the design process. MR also allows businesses to improve their risk management. Although the design process may seem relatively innocuous, several hazards might not be immediately apparent. “Some tools used in the prototyping process can be dangerous if not used properly,” says Sugar. “In mixed reality, you can complete even the most perilous parts of the design process without putting yourself at risk.” Another benefit of using MR technology in the design process is that it enables stronger collaboration. When teams work with paper blueprints or physical models/prototypes, they have to all be in the same place to work on their designs. With MR technology, teams from anywhere in the world can see and edit digital plans and models in real-time, connecting and working together despite being in different locations. This ensures everyone has access to the most up-to-date plans and designs. The time and cost savings involved with this alone are massive. Adopting any new technology, including mixed reality, comes with an upfront cost, and businesses would be wise to look at this as a strategic investment. While companies may have to spend money to buy new devices, they will save much more in the long run. By allowing workers to collaborate remotely more effectively, MR technology will save businesses significant sums on travel expenses — not to mention the time they will save with the convenience of these digitized processes. In the later stages of the design process, the immersive qualities of MR give designers more freedom in testing. “MR technology is an incredible tool for designers for processes like A/B testing,” Sugar asserts. “Best yet, the digital nature of the visualization means that designers can test new changes with minimal risk. It isn’t like physical prototyping, where making a change requires an investment in materials and could cause destruction if it backfires. Designers can have more freedom when using mixed reality technology.” Embrace the new MR paradigm Because of all of these benefits, many businesses have seen substantial positive impacts on their bottom line. “One report shows that organizations that adopted mixed reality technology saw a 4% annual increase in revenue, while another shows that more than 3 in 5 reported an ROI of 30% or more when using the technology for design and prototyping purposes,” Sugar explains. “These statistics make it clear that MR has a transformative potential within the business world.” With this in mind, companies that hope to reap the power of MR should embrace this new paradigm now while they have the opportunity to be ahead of the curve. “Now is the time to adopt MR technology,” concludes Sugar. “It will have a transformative impact on your company and its success.” From product design to interior design and construction, design is a fundamental part of everything we touch and everywhere we go. However, the design process is incredibly involved and requires a high level of attention to detail — even one mistake could cause the entire design to come crashing down — which is why many designers are constantly looking for innovations that will make their jobs better, more efficient, and safer. What is Mixed Reality (MR)? One powerful new technology seems destined to shake up the design landscape for the better: mixed reality (MR). Although people might be familiar with the concepts of virtual reality (VR) and augmented reality (AR), MR takes this technology’s capabilities to a different level and will change the design process for the better. MR is made possible through a combination of the most powerful features of VR and AR technology. Where VR provides a fully immersive digital environment, AR overlays digital content onto the real world. MR allows users to interact and engage with 3D virtual objects using natural movements and gestures due to the technology’s ability to map out the user’s actual environment. The result is that users can see and manipulate digital elements as if they were truly present in the same physical space. Greg Sugar, President of LineZero , a strategic technology consultancy specializing in helping businesses adopt the latest technology to enhance employee experience and improve operational efficiency, has firsthand experience seeing the influence of MR and has helped several organizations adopt it. LineZero LineZero “MR technology allows those in the design process to visualize and analyze many aspects of their designs,” Sugar explains. “This can be incredibly helpful in the pre-construction stage, as it allows designers to envision their designs before they enter construction. This technology allows you to not only see everything you’re working on but also interact with it.” How MR will help businesses improve their design processes How MR will help businesses improve their design processes While mixed reality may appear to be just another passing tech trend or a fancy toy, it actually presents a multitude of advantages for both employees and businesses. From employee engagement to enabling increased precision and safety, MR can be a transformative force in businesses’ design processes. For example, since MR technology allows designers to visualize their design and build prototypes before building them in real life, designers’ vision can be better communicated, and any potential flaws in the design can be identified and rectified early on. MR gives users access to real-time data and visual aids, reducing the likelihood of human error in the design process. This helps with the final quality of the products being designed as well as their safety and reliability. In industries where a great deal of precision is required, MR can help ensure attention to detail from the early stages of the design process. MR also allows businesses to improve their risk management. Although the design process may seem relatively innocuous, several hazards might not be immediately apparent. “Some tools used in the prototyping process can be dangerous if not used properly,” says Sugar. “In mixed reality, you can complete even the most perilous parts of the design process without putting yourself at risk.” Another benefit of using MR technology in the design process is that it enables stronger collaboration. When teams work with paper blueprints or physical models/prototypes, they have to all be in the same place to work on their designs. With MR technology, teams from anywhere in the world can see and edit digital plans and models in real-time, connecting and working together despite being in different locations. This ensures everyone has access to the most up-to-date plans and designs. The time and cost savings involved with this alone are massive. Adopting any new technology, including mixed reality, comes with an upfront cost, and businesses would be wise to look at this as a strategic investment. While companies may have to spend money to buy new devices, they will save much more in the long run. By allowing workers to collaborate remotely more effectively, MR technology will save businesses significant sums on travel expenses — not to mention the time they will save with the convenience of these digitized processes. In the later stages of the design process, the immersive qualities of MR give designers more freedom in testing. “MR technology is an incredible tool for designers for processes like A/B testing,” Sugar asserts. “Best yet, the digital nature of the visualization means that designers can test new changes with minimal risk. It isn’t like physical prototyping, where making a change requires an investment in materials and could cause destruction if it backfires. Designers can have more freedom when using mixed reality technology.” Embrace the new MR paradigm Embrace the new MR paradigm Because of all of these benefits, many businesses have seen substantial positive impacts on their bottom line. “One report shows that organizations that adopted mixed reality technology saw a 4% annual increase in revenue , while another shows that more than 3 in 5 reported an ROI of 30% or more when using the technology for design and prototyping purposes,” Sugar explains. “These statistics make it clear that MR has a transformative potential within the business world.” 4% annual increase in revenue 4% annual increase in revenue 30% or more 30% or more With this in mind, companies that hope to reap the power of MR should embrace this new paradigm now while they have the opportunity to be ahead of the curve. “Now is the time to adopt MR technology,” concludes Sugar. “It will have a transformative impact on your company and its success.”

Designing the Future: How Mixed Reality Is Transforming Project Planning and Design

ভবিষ্যত ডিজাইন করা: মিশ্র বাস্তবতা প্রকল্প পরিকল্পনা এবং নকশাকে কীভাবে রূপান্তরিত করছে

Die Zukunft gestalten: Wie Mixed Reality die Projektplanung und das Design verändert

Diseñando el futuro: cómo la realidad mixta está transformando la planificación y el diseño de proyectos

Concevoir l'avenir : comment la réalité mixte transforme la planification et la conception de projets

भविष्य की रूपरेखा: मिश्रित वास्तविकता किस प्रकार परियोजना नियोजन और डिजाइन को बदल रही है

未来をデザインする: 複合現実がプロジェクト計画と設計をどのように変革するか

미래 설계: 혼합 현실이 프로젝트 계획 및 설계를 어떻게 변화시키고 있습니까?

Projetando o futuro: como a realidade mista está transformando o planejamento e o design de projetos

Проектирование будущего: как смешанная реальность меняет планирование и дизайн проектов

Geleceği Tasarlamak: Karma Gerçeklik Proje Planlama ve Tasarımını Nasıl Dönüştürüyor?

Thiết kế tương lai: Thực tế hỗn hợp đang thay đổi việc lập kế hoạch và thiết kế dự án như thế nào

设计未来：混合现实如何改变项目规划和设计

This paper is available on arxiv under CC 4.0 license.
Authors:
(1) Oded Blumenthal, Software and Information Systems Engineering, Ben Gurion University, Israel;
(2) Guy Shani, Software and Information Systems Engineering, Ben Gurion University, Israel. Table of Links Introduction
Background
Related Work
POMCP for Stochastic Contingent Planning
Domain Independent Heuristics for POMCP
Empirical Evaluation
Conclusion and References 7 Conclusion In this paper we suggested to model goal POMDPs as stochastic contingent planning models, which allows us to use domain independent heuristics developed in the automated planning community to estimate the utility of belief states. We implemented our domain independent heuristics into the rollout mechanism of POMCP — a well known online POMDP planner that constructs a search tree to evaluate which action to take next. We provide an empirical evaluation showing how heuristics provide much leverage, especially in complex domains that require a long planning horizon, compared to the standard uniform rollout policy that is often used in POMCP. For future research we intend to integrate our methods into other solvers, such as RTDP-BEL, or into point-based planners as a method to gather good belief points. We can also experiment with additional heuristics, other than the hadd heuristic used in this paper. References [1] Alexandre Albore, Héctor Palacios & Hector Geffner (2009): A Translation-Based Approach to Contingent Planning. In: IJCAI, 9, pp. 1623–1628, doi:10.5555/1661445.1661706. Available at https://dl.acm. org/doi/10.5555/1661445.1661706. [2] Blai Bonet & Héctor Geffner (2001): Planning as heuristic search. Artificial Intelligence 129(1-2), pp. 5–33, doi:10.1016/S0004-3702(01)00108-4. [3] Blai Bonet & Hector Geffner (2009): Solving POMDPs: RTDP-Bel vs. Point-based Algorithms. In Craig Boutilier, editor: IJCAI 2009, Proceedings of the 21st International Joint Conference on Artificial Intelligence, Pasadena, California, USA, July 11-17, 2009, pp. 1641–1646, doi:10.5555/1661445.1661709. Available at https://dl.acm.org/doi/10.5555/1661445.1661709. [4] Blai Bonet & Hector Geffner (2011): Planning under Partial Observability by Classical Replanning: Theory and Experiments. In: IJCAI 2011, Proceedings of the 22nd International Joint Conference on Artificial Intelligence, Barcelona, Catalonia, Spain, July 16-22, 2011, pp. 1936–1941, doi:10.5591/978-1-57735-516-8/IJCAI11-324. [5] Ronen I Brafman & Guy Shani (2016): Online belief tracking using regression for contingent planning. Artificial Intelligence 241, pp. 131–152, doi:10.1016/j.artint.2016.08.005. [6] Hector Geffner & Blai Bonet (2022): A concise introduction to models and methods for automated planning. Springer Nature. [7] Malte Helmert & Carmel Domshlak (2009): Landmarks, Critical Paths and Abstractions: What’s the Difference Anyway? In Lubos Brim, Stefan Edelkamp, Eric A. Hansen & Peter Sanders, editors: Graph Search Engineering, 29.11. - 04.12.2009, Dagstuhl Seminar Proceedings 09491, Schloss Dagstuhl -LeibnizZentrum für Informatik, Germany, doi:10.1609/icaps.v19i1.13370. Available at http://drops.dagstuhl. de/opus/volltexte/2010/2432/. [8] Malte Helmert, Patrik Haslum, Jörg Hoffmann & Raz Nissim (2014): Merge-and-shrink abstraction: A method for generating lower bounds in factored state spaces. Journal of the ACM (JACM) 61(3), pp. 1–63, doi:10.1145/2559951. [25] Guy Shani, Joelle Pineau & Robert Kaplow (2013): A survey of point-based POMDP solvers. Autonomous Agents and Multi-Agent Systems 27, pp. 1–51, doi:10.1007/s10458-012-9200-2. [26] William Shen, Felipe Trevizan, Sam Toyer, Sylvie Thiébaux & Lexing Xie (2019): Guiding search with generalized policies for probabilistic planning. In: Proceedings of the International Symposium on Combinatorial Search, 10, pp. 97–105, doi:10.1609/socs.v10i1.18507. [27] David Silver & Joel Veness (2010): Monte-Carlo planning in large POMDPs. Advances in neural information processing systems 23, doi:10.5555/2997046.2997137. [28] Richard D Smallwood & Edward J Sondik (1973): The optimal control of partially observable Markov processes over a finite horizon. Operations research 21(5), pp. 1071–1088, doi:10.1287/opre.21.5.1071. [29] Adhiraj Somani, Nan Ye, David Hsu & Wee Sun Lee (2013): DESPOT: Online POMDP planning with regularization. Advances in neural information processing systems 26, doi:10.1613/jair.5328. [30] Zachary Sunberg & Mykel Kochenderfer (2018): Online algorithms for POMDPs with continuous state, action, and observation spaces. In: Proceedings of the International Conference on Automated Planning and Scheduling, 28, pp. 259–263, doi:10.48550/arXiv.1709.06196. [31] Yuchen Xiao, Sammie Katt, Andreas ten Pas, Shengjian Chen & Christopher Amato (2019): Online planning for target object search in clutter under partial observability. In: 2019 International Conference on Robotics and Automation (ICRA), IEEE, pp. 8241–8247, doi:10.1109/ICRA.2019.8793494. [32] Nan Ye, Adhiraj Somani, David Hsu & Wee Sun Lee (2017): DESPOT: Online POMDP planning with regularization. Journal of Artificial Intelligence Research 58, pp. 231–266, doi:10.1613/jair.5328. This paper is available on arxiv under CC 4.0 license. Authors: (1) Oded Blumenthal, Software and Information Systems Engineering, Ben Gurion University, Israel; (2) Guy Shani, Software and Information Systems Engineering, Ben Gurion University, Israel. This paper is available on arxiv under CC 4.0 license. Authors: Authors: (1) Oded Blumenthal, Software and Information Systems Engineering, Ben Gurion University, Israel; (2) Guy Shani, Software and Information Systems Engineering, Ben Gurion University, Israel. Table of Links Introduction Background Related Work POMCP for Stochastic Contingent Planning Domain Independent Heuristics for POMCP Empirical Evaluation Conclusion and References Introduction Introduction Background Background Related Work Related Work POMCP for Stochastic Contingent Planning POMCP for Stochastic Contingent Planning Domain Independent Heuristics for POMCP Domain Independent Heuristics for POMCP Empirical Evaluation Empirical Evaluation Conclusion and References Conclusion and References 7 Conclusion In this paper we suggested to model goal POMDPs as stochastic contingent planning models, which allows us to use domain independent heuristics developed in the automated planning community to estimate the utility of belief states. We implemented our domain independent heuristics into the rollout mechanism of POMCP — a well known online POMDP planner that constructs a search tree to evaluate which action to take next. We provide an empirical evaluation showing how heuristics provide much leverage, especially in complex domains that require a long planning horizon, compared to the standard uniform rollout policy that is often used in POMCP. For future research we intend to integrate our methods into other solvers, such as RTDP-BEL, or into point-based planners as a method to gather good belief points. We can also experiment with additional heuristics, other than the h add heuristic used in this paper. add References [1] Alexandre Albore, Héctor Palacios & Hector Geffner (2009): A Translation-Based Approach to Contingent Planning. In: IJCAI, 9, pp. 1623–1628, doi:10.5555/1661445.1661706. Available at https://dl.acm. org/doi/10.5555/1661445.1661706. [2] Blai Bonet & Héctor Geffner (2001): Planning as heuristic search. Artificial Intelligence 129(1-2), pp. 5–33, doi:10.1016/S0004-3702(01)00108-4. [3] Blai Bonet & Hector Geffner (2009): Solving POMDPs: RTDP-Bel vs. Point-based Algorithms. In Craig Boutilier, editor: IJCAI 2009, Proceedings of the 21st International Joint Conference on Artificial Intelligence, Pasadena, California, USA, July 11-17, 2009, pp. 1641–1646, doi:10.5555/1661445.1661709. Available at https://dl.acm.org/doi/10.5555/1661445.1661709. [4] Blai Bonet & Hector Geffner (2011): Planning under Partial Observability by Classical Replanning: Theory and Experiments. In: IJCAI 2011, Proceedings of the 22nd International Joint Conference on Artificial Intelligence, Barcelona, Catalonia, Spain, July 16-22, 2011, pp. 1936–1941, doi:10.5591/978-1-57735-516-8/IJCAI11-324. [5] Ronen I Brafman & Guy Shani (2016): Online belief tracking using regression for contingent planning. Artificial Intelligence 241, pp. 131–152, doi:10.1016/j.artint.2016.08.005. [6] Hector Geffner & Blai Bonet (2022): A concise introduction to models and methods for automated planning. Springer Nature. [7] Malte Helmert & Carmel Domshlak (2009): Landmarks, Critical Paths and Abstractions: What’s the Difference Anyway? In Lubos Brim, Stefan Edelkamp, Eric A. Hansen & Peter Sanders, editors: Graph Search Engineering, 29.11. - 04.12.2009, Dagstuhl Seminar Proceedings 09491, Schloss Dagstuhl -LeibnizZentrum für Informatik, Germany, doi:10.1609/icaps.v19i1.13370. Available at http://drops.dagstuhl. de/opus/volltexte/2010/2432/. [8] Malte Helmert, Patrik Haslum, Jörg Hoffmann & Raz Nissim (2014): Merge-and-shrink abstraction: A method for generating lower bounds in factored state spaces. Journal of the ACM (JACM) 61(3), pp. 1–63, doi:10.1145/2559951. [25] Guy Shani, Joelle Pineau & Robert Kaplow (2013): A survey of point-based POMDP solvers. Autonomous Agents and Multi-Agent Systems 27, pp. 1–51, doi:10.1007/s10458-012-9200-2. [26] William Shen, Felipe Trevizan, Sam Toyer, Sylvie Thiébaux & Lexing Xie (2019): Guiding search with generalized policies for probabilistic planning. In: Proceedings of the International Symposium on Combinatorial Search, 10, pp. 97–105, doi:10.1609/socs.v10i1.18507. [27] David Silver & Joel Veness (2010): Monte-Carlo planning in large POMDPs. Advances in neural information processing systems 23, doi:10.5555/2997046.2997137. [28] Richard D Smallwood & Edward J Sondik (1973): The optimal control of partially observable Markov processes over a finite horizon. Operations research 21(5), pp. 1071–1088, doi:10.1287/opre.21.5.1071. [29] Adhiraj Somani, Nan Ye, David Hsu & Wee Sun Lee (2013): DESPOT: Online POMDP planning with regularization. Advances in neural information processing systems 26, doi:10.1613/jair.5328. [30] Zachary Sunberg & Mykel Kochenderfer (2018): Online algorithms for POMDPs with continuous state, action, and observation spaces. In: Proceedings of the International Conference on Automated Planning and Scheduling, 28, pp. 259–263, doi:10.48550/arXiv.1709.06196. [31] Yuchen Xiao, Sammie Katt, Andreas ten Pas, Shengjian Chen & Christopher Amato (2019): Online planning for target object search in clutter under partial observability. In: 2019 International Conference on Robotics and Automation (ICRA), IEEE, pp. 8241–8247, doi:10.1109/ICRA.2019.8793494. [32] Nan Ye, Adhiraj Somani, David Hsu & Wee Sun Lee (2017): DESPOT: Online POMDP planning with regularization. Journal of Artificial Intelligence Research 58, pp. 231–266, doi:10.1613/jair.5328.

Rollout Heuristics for Online Stochastic Contingent Planning: Conclusion and References

This paper is available on arxiv under CC 4.0 license.
Authors:
(1) Oded Blumenthal, Software and Information Systems Engineering, Ben Gurion University, Israel;
(2) Guy Shani, Software and Information Systems Engineering, Ben Gurion University, Israel. Table of Links Introduction
Background
Related Work
POMCP for Stochastic Contingent Planning
Domain Independent Heuristics for POMCP
Empirical Evaluation
Conclusion and References 2 Background We now provide the required background on POMDPs, contingent planning, domain-independent heuristics, and the POMCP algorithm. 2.1 POMDPs Because the state of a POMDP is partially observable, the agent typically does not know what the true underlying state of the world is. Hence, it can maintain a belief state b, which is a distribution over S, i.e., b(s) is the likelihood that s is the current state. When a goal belief is reached, that is sums∈Gb(s) = 1, then the agent is sure that it is at a goal state, and the execution terminates. A solution to a POMDP, called a policy, is a function that assigns an action to every belief state. The optimal policy minimizes the expected cost, i.e., the expected number of steps before a goal belief has been reached. 2.2 POMCP The Partially Observable Monte-Carlo Planning (POMCP) online re-planning approach uses a Monte Carlo tree search (MCTS) approach to select the next action to execute [27]. At each re-planning episode POMCP constructs a tree, where the root node is the current belief state. Then, POMCP runs forward simulations, where a state is sampled from the current belief, and actions are chosen using an exploration strategy that initially selects actions that were not executed a sufficient amount of times, but gradually moves to select the seemingly best action. Observations in the simulations are selected based on the current state-action observation distribution. When reaching a leaf node, POMCP begins a so-called rollout. This rollout is designed to provide a value estimate for the leaf, based on some predefined rollout policy. The value of the leaf is updated using the outcome of the rollout, and then the values of the nodes along the branch that were visited during the simulation are updated given their descendants. Obviously, the values of all nodes in the tree are hence highly dependent on the values obtained by the rollout policy. POMCP is an anytime algorithm, that is, it continues to run simulations until a timeout, and then returns the action that seems best at the root of the search tree. POMCP was designed for large problems. Hence, POMCP does not maintain and update a belief state explicitly. Instead, POMCP uses a particle filter approach, where a set of states is sampled at the initial belief, and this set is progressed through the tree. 2.3 Contingent Planning under Partial Observability Preconditions allow us to restrict our attention only to applicable actions. An action is applicable in a belief b is all possible states in b satisfy the preconditions of the action. Obviously, one can avoid specifying preconditions for actions, allowing for actions that can always be executed, as is typically the case in flat POMDP representations. However, in domains with many actions, preconditions are a useful tool for drastically limiting the amount of actions that should be considered. 2.4 Regression-based Belief Maintenance Updating a belief can be costly. Alternatively, one can avoid the computation of new formulas representing the updated belief, by maintaining only the initial belief formula, and the history —the sequence of executed actions and sensed observations [5]. When the agent needs to query whether the preconditions of an action or the goal hold at the current node, the formula is regressed [20] through the action observation sequence back towards the initial belief. Then, one can apply SAT queries to check whether the query formula holds. We now briefly review the regression process for deterministic actions. This approach can be highly useful for larger POMDPs, complementing the particle filter approach used in POMCP. Regression maintains the equivalence of the formula [20, 5]. For any two formulas φ1 and φ2 we have: Hence, we can produce a regression over formulas, and compare the regressed formulas, making conclusions about the original formulas. The regression can be recursively applied to a sequence of actions and observations (history) h as follows: where ε is the empty sequence. This allows us to perform a regression of a formula through an entire plan, and analyze the required conditions for a plan to apply. In addition, the regression mechanism of [5] maintains a cached list of fluents F(n) that are known to hold at node n, given the action effects or observations. Following an actuation action a, F(a(n)) contains all fluents in F(n) that were not modified by a, as well as effects of a that are not conditioned on hidden fluents. For a sensing action revealing the value l, F(a(n,l)) = F(n) ∪ {l}. During future regression queries, when a value at a particular node becomes known, e.g. when regressing a later observation, it is added to F(n). All fluents p such that p ∈/ F(n)∧ ¬p ∈/ F(n) are said to be hidden at n. The cached list is useful for simplifying future regressed formulas. This paper is available on arxiv under CC 4.0 license. Authors: (1) Oded Blumenthal, Software and Information Systems Engineering, Ben Gurion University, Israel; (2) Guy Shani, Software and Information Systems Engineering, Ben Gurion University, Israel. This paper is available on arxiv under CC 4.0 license. Authors: Authors: (1) Oded Blumenthal, Software and Information Systems Engineering, Ben Gurion University, Israel; (2) Guy Shani, Software and Information Systems Engineering, Ben Gurion University, Israel. Table of Links Introduction Background Related Work POMCP for Stochastic Contingent Planning Domain Independent Heuristics for POMCP Empirical Evaluation Conclusion and References Introduction Introduction Background Background Related Work Related Work POMCP for Stochastic Contingent Planning POMCP for Stochastic Contingent Planning Domain Independent Heuristics for POMCP Domain Independent Heuristics for POMCP Empirical Evaluation Empirical Evaluation Conclusion and References Conclusion and References 2 Background We now provide the required background on POMDPs, contingent planning, domain-independent heuristics, and the POMCP algorithm. 2.1 POMDPs Because the state of a POMDP is partially observable, the agent typically does not know what the true underlying state of the world is. Hence, it can maintain a belief state b, which is a distribution over S, i.e., b(s) is the likelihood that s is the current state. When a goal belief is reached, that is sums∈Gb(s) = 1, then the agent is sure that it is at a goal state, and the execution terminates. A solution to a POMDP, called a policy, is a function that assigns an action to every belief state. The optimal policy minimizes the expected cost, i.e., the expected number of steps before a goal belief has been reached. 2.2 POMCP The Partially Observable Monte-Carlo Planning (POMCP) online re-planning approach uses a Monte Carlo tree search (MCTS) approach to select the next action to execute [27]. At each re-planning episode POMCP constructs a tree, where the root node is the current belief state. Then, POMCP runs forward simulations, where a state is sampled from the current belief, and actions are chosen using an exploration strategy that initially selects actions that were not executed a sufficient amount of times, but gradually moves to select the seemingly best action. Observations in the simulations are selected based on the current state-action observation distribution. When reaching a leaf node, POMCP begins a so-called rollout. This rollout is designed to provide a value estimate for the leaf, based on some predefined rollout policy. The value of the leaf is updated using the outcome of the rollout, and then the values of the nodes along the branch that were visited during the simulation are updated given their descendants. Obviously, the values of all nodes in the tree are hence highly dependent on the values obtained by the rollout policy. POMCP is an anytime algorithm, that is, it continues to run simulations until a timeout, and then returns the action that seems best at the root of the search tree. POMCP was designed for large problems. Hence, POMCP does not maintain and update a belief state explicitly. Instead, POMCP uses a particle filter approach, where a set of states is sampled at the initial belief, and this set is progressed through the tree. 2.3 Contingent Planning under Partial Observability Preconditions allow us to restrict our attention only to applicable actions. An action is applicable in a belief b is all possible states in b satisfy the preconditions of the action. Obviously, one can avoid specifying preconditions for actions, allowing for actions that can always be executed, as is typically the case in flat POMDP representations. However, in domains with many actions, preconditions are a useful tool for drastically limiting the amount of actions that should be considered. 2.4 Regression-based Belief Maintenance Updating a belief can be costly. Alternatively, one can avoid the computation of new formulas representing the updated belief, by maintaining only the initial belief formula, and the history —the sequence of executed actions and sensed observations [5]. When the agent needs to query whether the preconditions of an action or the goal hold at the current node, the formula is regressed [20] through the action observation sequence back towards the initial belief. Then, one can apply SAT queries to check whether the query formula holds. We now briefly review the regression process for deterministic actions. This approach can be highly useful for larger POMDPs, complementing the particle filter approach used in POMCP. Regression maintains the equivalence of the formula [20, 5]. For any two formulas φ1 and φ2 we have: Hence, we can produce a regression over formulas, and compare the regressed formulas, making conclusions about the original formulas. The regression can be recursively applied to a sequence of actions and observations (history) h as follows: where ε is the empty sequence. This allows us to perform a regression of a formula through an entire plan, and analyze the required conditions for a plan to apply. In addition, the regression mechanism of [5] maintains a cached list of fluents F(n) that are known to hold at node n, given the action effects or observations. Following an actuation action a, F(a(n)) contains all fluents in F(n) that were not modified by a, as well as effects of a that are not conditioned on hidden fluents. For a sensing action revealing the value l, F(a(n,l)) = F(n) ∪ {l}. During future regression queries, when a value at a particular node becomes known, e.g. when regressing a later observation, it is added to F(n). All fluents p such that p ∈/ F(n)∧ ¬p ∈/ F(n) are said to be hidden at n. The cached list is useful for simplifying future regressed formulas.

Rollout Heuristics for Online Stochastic Contingent Planning: Background

This paper is available on arxiv under CC 4.0 license.
Authors:
(1) Oded Blumenthal, Software and Information Systems Engineering, Ben Gurion University, Israel;
(2) Guy Shani, Software and Information Systems Engineering, Ben Gurion University, Israel. Table of Links Introduction
Background
Related Work
POMCP for Stochastic Contingent Planning
Domain Independent Heuristics for POMCP
Empirical Evaluation
Conclusion and References 6 Empirical Evaluation We conduct an empirical study to evaluate our methods. Our methods are implemented in C#. 6.1 Benchmark Domains We extended the following contingent planning benchmarks to stochastic settings: Doors: In the door domain the agent must move in a grid to reach a target position. Odd levels in the grid are all open, while in even levels there are doors, and only one door is open. The agent can sense whether a door is open when it is at adjacent cells. The agent must identify the open doors and get to the target position. In the stochastic version the agent can open a closed door with some probability of success. The agent can hence either search for the already open door, or attempt to open a closed door. Blocks World: In the contingent blocks world problem, the agent does not know the structure of the initial block configuration, but it can sense whether one block is on top of another one, and whether a block is clear. In the stochastic version moving a block from one block to another has a 0.3 probability of success, while moving blocks to and from the table succeeds deterministicly. Hence, it is often preferable to use the table as an intermediate position. Unix: In this domain the agent must search for a file in a file system, and copy it to a destination folder. In the stochastic version there is a non-uniform distribution over the possible locations of the file. MedPks: The agent here needs to identify which illness a patient has and treat it. To do so, the agent tests for each illness independently, until the proper illness is found. The stochastic version here has non-uniform distribution over the possible illnesses as well. Localize: In this domain the agent must reach a goal position in a grid. The agent does not know where it initially is, and can only sense adjacent walls. In the stochastic version there several places in the grid where the agent may slip and stay in place. This makes the localization in the grid more difficult. Wumpus: In this challenging problem the agent must reach a target position in a grid infested by monsters called Wumpuses. Cells may be unsafe to travel as they may contain either a Wumpus or a pit. Wumpuses emit a stench, and pits emit a breeze, both of which can be sensed in adjacent cells. The agent must sense in multiple positions to identify the safe cells. The stochastic version here also has non-uniform distribution over the safe cells. 6.2 Results For each domain above we run 20 online episodes, and compute the success rate, the average run time for computing the next action, and the average cost to the goal. We did not use a timeout, but runs longer than 100 steps were considered to be stuck in a loop, and terminated. We begin by looking at the quality of the policy — the average cost to the goal. As can be seen, the random rollout policy is best only in the MedPks domain, and close to best in unix. This is not too surprising, because in these two domains the best strategy is very simple, and random strategies easily stumble upon the goal. In blocks all methods achieved similar performance, because the optimal strategy is very short, and rollouts are less important. This domain has many possible actions, and hence a huge branching factor, making it difficult to scale up using POMCP. On doors and localize, which require lengthier trajectories to reach the goal, but do not need long information-gathering efforts, the single state hadd strategy operates very well. However, on Wumpus, where long sequences of actions are needed for information gathering, the multiple-state heuristic works best. We expected the results to be that way, although we expected more significant difference between the "smart" heuristics and the random rollout. With respect to the required time to run the simulations for a single decision, the results are mixed. While obviously the random strategy requires no time to compute the next action during a rollout, it often results in lengthy rollouts, which reduce this effect. The single state heuristic is almost always faster than the multi-state heuristic, but not by much. This paper is available on arxiv under CC 4.0 license. Authors: (1) Oded Blumenthal, Software and Information Systems Engineering, Ben Gurion University, Israel; (2) Guy Shani, Software and Information Systems Engineering, Ben Gurion University, Israel. This paper is available on arxiv under CC 4.0 license. Authors: Authors: (1) Oded Blumenthal, Software and Information Systems Engineering, Ben Gurion University, Israel; (2) Guy Shani, Software and Information Systems Engineering, Ben Gurion University, Israel. Table of Links Introduction Background Related Work POMCP for Stochastic Contingent Planning Domain Independent Heuristics for POMCP Empirical Evaluation Conclusion and References Introduction Introduction Background Background Related Work Related Work POMCP for Stochastic Contingent Planning POMCP for Stochastic Contingent Planning Domain Independent Heuristics for POMCP Domain Independent Heuristics for POMCP Empirical Evaluation Empirical Evaluation Conclusion and References Conclusion and References 6 Empirical Evaluation We conduct an empirical study to evaluate our methods. Our methods are implemented in C#. 6.1 Benchmark Domains We extended the following contingent planning benchmarks to stochastic settings: Doors : In the door domain the agent must move in a grid to reach a target position. Odd levels in the grid are all open, while in even levels there are doors, and only one door is open. The agent can sense whether a door is open when it is at adjacent cells. The agent must identify the open doors and get to the target position. In the stochastic version the agent can open a closed door with some probability of success. The agent can hence either search for the already open door, or attempt to open a closed door. Doors Blocks World: In the contingent blocks world problem, the agent does not know the structure of the initial block configuration, but it can sense whether one block is on top of another one, and whether a block is clear. In the stochastic version moving a block from one block to another has a 0.3 probability of success, while moving blocks to and from the table succeeds deterministicly. Hence, it is often preferable to use the table as an intermediate position. Unix: In this domain the agent must search for a file in a file system, and copy it to a destination folder. In the stochastic version there is a non-uniform distribution over the possible locations of the file. MedPks : The agent here needs to identify which illness a patient has and treat it. To do so, the agent tests for each illness independently, until the proper illness is found. The stochastic version here has non-uniform distribution over the possible illnesses as well. MedPks Localize : In this domain the agent must reach a goal position in a grid. The agent does not know where it initially is, and can only sense adjacent walls. In the stochastic version there several places in the grid where the agent may slip and stay in place. This makes the localization in the grid more difficult. Localize Wumpus : In this challenging problem the agent must reach a target position in a grid infested by monsters called Wumpuses. Cells may be unsafe to travel as they may contain either a Wumpus or a pit. Wumpuses emit a stench, and pits emit a breeze, both of which can be sensed in adjacent cells. The agent must sense in multiple positions to identify the safe cells. The stochastic version here also has non-uniform distribution over the safe cells. Wumpus 6.2 Results For each domain above we run 20 online episodes, and compute the success rate, the average run time for computing the next action, and the average cost to the goal. We did not use a timeout, but runs longer than 100 steps were considered to be stuck in a loop, and terminated. We begin by looking at the quality of the policy — the average cost to the goal. As can be seen, the random rollout policy is best only in the MedPks domain, and close to best in unix. This is not too surprising, because in these two domains the best strategy is very simple, and random strategies easily stumble upon the goal. In blocks all methods achieved similar performance, because the optimal strategy is very short, and rollouts are less important. This domain has many possible actions, and hence a huge branching factor, making it difficult to scale up using POMCP. On doors and localize, which require lengthier trajectories to reach the goal, but do not need long information-gathering efforts, the single state h add strategy operates very well. However, on Wumpus, where long sequences of actions are needed for information gathering, the multiple-state heuristic works best. We expected the results to be that way, although we expected more significant difference between the "smart" heuristics and the random rollout. add With respect to the required time to run the simulations for a single decision, the results are mixed. While obviously the random strategy requires no time to compute the next action during a rollout, it often results in lengthy rollouts, which reduce this effect. The single state heuristic is almost always faster than the multi-state heuristic, but not by much.

Rollout Heuristics for Online Stochastic Contingent Planning: Empirical Evaluation

Stories, News & Mentions about PLANNY

Planny’s Stories on HackerNoon