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Tavern Lecture Two: A Fantastical Discourse on NFTs, Tokens, Milk, and an Inebriated NFT Avatar

Lead image from the 2018 movie Ready Player One, directed by Steven Spielberg and based on the book of the same name written by Ernest Cline. Ready Player One tells a story set in a virtual world called “The Oasis”. This was pretty much what I have wanted since I could conceive such a concept. And I really, really want this fantasy realised. The movie’s opening minutes set up the Oasis as the ultimate virtual world, as the camera pans from Minecraft to outlandish golf courses to space-Vegas before ending in on Planet Doom, a planet playing host to a seemingly endless Deathmatch. It’s there where we see one of the movie’s main characters score kills with the Assault Rifle from Halo and a side character wearing Starcraft’s Terran Marine armour in over-the-top USA livery. The movie might have been self-indulgent and a little vapid but it showed the potential that a Metaverse might have. The Oasis is full of highly diverse experiences ranging from competitive shooting to racing and even to hang-gliding through some crazy-looking experiences. With the entire foundation for a game already made, it makes sense that some people set off to create specific, enjoyable activities that would be too costly to develop in isolation. It’s full of social spaces specifically designed for players to hang about in. Not many games have that built in. The closest analogue for this, in my experience, is Limsa Lominsa in Final Fantasy XIV. The city’s central Aetheryte Plaza is generally full of people dancing, chatting and playing music. In essence, interacting with each other with the social tools available to them. The Oasis has its own Zero-G disco, casinos and even libraries for players to make use of. Ready Player One’s depiction of in-game social interaction does rely on technology we haven’t invented yet, which makes it hard to compare otherwise. The last thing that the Oasis does is to blur the line between player and developer. While the movie doesn’t really go into specifics, currency in the game can be converted for use in the real world.  One character in the movie builds a replica of the Iron Giant to sell to other players. Another makes a living off selling items looted from players he’s killed. It created its own economy that affects the real world. The same thing probably won’t happen in reality but it is a nice idea. The Oasis seems like the stuff of fantasy and, like faster-than-light travel, may never truly exist. Where could one find the combination of all that content, social interaction and incentive for creation in the real world? The Current standard in gaming’s Metaverses We’ve got all of that, actually. In Roblox. I had played a fair bit of Roblox over the last few months to write some articles about the fascinating platform (you can read about my discoveries here) and what I found was that Roblox itself is something of a crude Metaverse. The platform is designed as a host for user-generated content with the vast majority of the game’s content being made by players for other players to enjoy. Players can dress themselves up however they want thanks to a robust clothing Catalogue stocked with items made by players and can end up looking like a fairy princess or a US Marine or anything in between. They can then take these avatars into games based on our reality like a restaurant tycoon game or into an anime crossover game more unhinged than Jump Force. Just like the Oasis, there are separate experiences that cater to specific types of players, a huge range of activities to enjoy, and even some social spaces to explore. It’s really great except for two things. The first is that it is Roblox which means intense monetisation targeted at users. As unbelievable as it sounds, gacha games feel less predatory than Roblox. Most games aggressively peddle premium membership and offer rewards for spending real-world cash for in-game power. It is this model that has made Roblox as accessible as it is, however. Roblox has a few ways to let its creators earn money from their content from simply selling items in their experiences or from having premium players turn up. This model pays out so well, a pair of teenagers earn six figures a year and paid off their parent’s mortgage from their earnings. The second is that Roblox is old and practically creaks every time a button is pressed. Most textures looked dated a decade ago and animations are practically non-existent. This isn’t really a shortcoming that Roblox can easily overcome. It came out in 2006, after all. To make it worse, not many of Roblox’s experiences have the same level of polish and depth as a conventional game. Even the best Roblox experiences feel like pale imitations of actual games with copies of mechanics seeming to exist solely to check a box and without an entire game to make full use of them. The Rainbow Six-inspired shooting framework applied to a game centered around avoiding Anime mascots in Area 51 comes to mind here. What lies in the Future of the Gaming Metaverse? Getting a shinier, fresher platform to host a Gaming Multiverse relies on finding the money to make the framework and attracting more people to make the content necessary for a metaverse. There’ve been two new attempts to create such a thing. The first attempt is , a Non-Fungible Token (NFT) and blockchain-based platform that has already seen support from franchises like The Walking Dead and organisations like the South China Morning Post. The Sandbox It uses a lot of buzzwords but The Sandbox claims its system will help creators monetise their content through its own cryptocurrency and by using NFTs to control the supply. In essence, each asset created in the Sandbox is a finite resource that only exists in a limited quantity, unlike the infinite copies created in Roblox. With luck, The Sandbox might be able to unseat Roblox as the poster child of metaverses. NFTs could well realise the user-driven economy alluded to in Ready Player One with talented creators selling unique copies of their work to other users. Its standardised creation tools could enable players to carry over equipment and items from one experience to another. There is a chance that it could be the voxel-based Gaming Metaverse of the present. The second attempt is Facebook’s newly announced foray into developing a metaverse. This attempt has just been announced and there isn’t as much known about it compared to the Sandbox but it has Facebook’s mountains of cash behind it so it probably won’t be that far off. I can’t wait for a more digitised future as more and more of my childhood fantasies are slowly coming into being. Whether it might be The Sandbox’s model or whatever Facebook comes up with or any other competitor, I want in. This article is part of The Gaming Metaverse Writing Contest hosted by HackerNoon in partnership with . The Sandbox Submit your #gaming-metaverse story today for your chance to win up to $2000 in SAND tokens.

Please, God, Give Me a Gaming Metaverse

Ever watched Ready Player One and wondered what it would be like to have the same thing in real life (well you know what we mean)? Play around a virtual casino, explore online megastructures, party at a metaverse club, race digital collectible cars with friends from around the world – all from the comfort of your couch. Well there’s always Minecraft, Roblox and Second Life. So, what’s missing? The names mentioned are run on permissioned systems and can be turned off at the flick of a switch. There is little that participants can do if that happens. In spite of the open sandbox nature of these games, players are often governed by policies in which they play no part for the decision-making process. Plus, financial transactions (or micro-transactions) in these games are neither immutable nor integrated into the gameplay with real world finance. Metaverses allow imaginations to run wild What we need is the assurance of an unstoppable game engine backed by decentralised governance and topped up with the immersive experience of on-chain transactions through seamless wallet interactions. So is there a permission-less Ready Player One experience with gamified finance available right now? My co-author Rohit and I set out to find out exactly this. And we found that there are some projects that are already building trust-less metaverses – , , etc. The oldest and most intricate among these yet is Decentraland. Decentraland Cryptovoxels The Sandbox The past few weeks have been crazy in the real world with Elon Musk pumping $DOGE memes, Tesla announcing their Bitcoin investment and r/wallstreetbets one-upping Wall Street vis-à-vis $GME, $AMC et al. But Rohit and I discovered crazier experiences in the virtual world called Decentraland. Here are some of the funnest things we found in there: Decentral Games One of the opening shots in Ready Player One was that of “a casino the size of a planet” in OASIS. In Decentraland, you are spoilt for choice. There are multiple casinos in the Vegas City District run by – the first social metaverse casino where anyone can be the house. Decentral Games There are currently 3 operational venues where you can try your luck viz. Chateau Satoshi ( ), Tominoya ( ) and Serenity Island ( ). Early disclaimer for anyone trying it out: you can play in Decentral Games only if your physical jurisdiction allows gambling. -75, 77 -119, 133 -145, 115 Decentral Games is owned by its users who participate in decision-making by staking $DG, its native token. Even the treasury decisions are taken through user-voting in the DAO (decentralized autonomous organization). The DAO currently holds millions of dollars’ worth of assets in LAND parcels, NFTs and $DG in its community wallet. The community can create and vote on proposals to build casinos, games, art galleries etc. using these funds. $DG is earned by playing games with $MANA and $DAI (also referred to as gameplay mining), through liquidity farming and from governance rewards. Ready Player One’s OASIS had one, Decentraland has three (for now) Launched in 2019, the project is backed by Digital Currency Group, Cluster Capital, Hiraku etc. Currently, one can play blackjack, roulette, slots and backgammon in there. The next game to be launched is Texas hold ‘em poker, and then Baccarat later. Apart from standalone games, the casinos also host events like NFT auctions and casino night parties. We missed attending the latest NFT auction which saw an Elon Musk-featured artwork sell for 10+ ETH. Ethereum chain bottlenecks are avoided since transactions are executed on the Matic sidechain and any gas fees are covered by Decentral Games itself. So, players don’t need to worry about gas or block confirmation delays. Leaderboards in Ready Player One v/s Decentral Games We caught up with Decentral Games’ founder and project lead Miles Anthony to chat on the user metrics. He said, “On a typical event day, we have about 300 players playing both free-to-play games and also games played with $MANA and $DAI. The total bets have exceeded USD 20 million since launch and we are scaling the platform to accommodate the demands….we are definitely seeing numbers of users ramping up exponentially!”. The platform also has USD 7+ million in TVL (total value locked) by investors currently. The crew has plans to add support for $USDT and $USDC, a new Cyberpunk-themed casino, community and private poker lounges and celebrity poker tournaments for charity. Battle Racers Decentraland has something to offer for the adrenaline junkies as well. Head to district ( ) to experience blockchain powered arcade racing, courtesy . An action packed game where you can design, build and race model cars on arcade-sized tracks, Battle Racers lets you put your (virtual) driving skills to the fore. 67, -21 Battle Racers You can customize your race cars as per your needs, even fitting it with weapons to use your combat skills and annihilate your opponents. Being the first to the finish line need not be the only way to win a race here! Preparing to race Battle Racers has been developed by , a leading mobile and blockchain game studio based in Manila. The company was founded by veterans of the Southeast Asian game industry in 2014, and currently has 40+ developers. Some of their other popular titles include ‘Kung Fu Clicker’, ‘Holy Ship!’ and ‘Mushroom Mania’. Altitude Games You can enter the Battle Racers area to join the competitive races, just drive around on your own, customize your cars in the garage, or simply hang around as a spectator and enjoy the action. The garage has a range of available parts with different stats and skills, all of which contribute to your car’s overall performance. Battle Racers car parts on sale in the OpenSea marketplace Battle Racers also enables users to tokenize their designed car into a Non-Fungible Token (NFT), and create a digital asset that will permanently reside on the blockchain. The win/loss history of tokenized cars is continuously tracked on the blockchain. Consequently, the stats of such cars keep on improving as they compete in more races as compared to “off-chain” cars. Players also stand to earn more points when they race with such “on-chain” cars. And if that’s not all, you can even sell (or buy) tokenized cars on the Marketplace using Decentraland’s native $MANA token. Sugar Club How do netizens of Decentraland relax after a hard week of doing crypto? By hitting the Sugar Club, of course! Located in district ( ), the nightclub Sugar Club is one of the most happening places and a regular meetup joint in the Decentraland metaverse. -1, -35 It has already created its unique flavour and distinct style, and has proved to be an instant hit among folks looking for a good time. Unlike the other projects featured here, Sugar Club is the brainchild of a sole developer who goes by the name of Kay, and isn’t backed by any team. You can watch this to get more insights into his work and how he came up with this idea. YouTube interview Ready Player One's Distracted Globe v/s Decentraland's Sugar Club Sugar Club features a glowing purple floor and some of the best electro music in the Metaverse to help you let your hair down. If you’re tired of all the dancing and chatting, then you can stroll down to the digital art gallery, which features the latest creations from crypto-artists and visual creators. One strange aspect of Sugar Club is that even though the dance floor might be full, you might hardly see a crowd. This is due to the way the Decentraland platform has been designed. When users enter Decentraland, they are split into multiple nodes or servers. So, even if two users enter the Club simultaneously, they can be on different servers and invisible to each other! At the Sugar Club, you can spend your $MANA to buy crypto-drinks for yourself or for the lady at the bar. You can even use your $MANA to upgrade your seating place or access a wider pool of music to choose from. Train Transit System Any Metaverse requires a modern transit system to ferry around its netizens. In South Decentraland, we have the Trail Transit System designed by , a 3-D art studio and a known name in Decentraland. Polygonal Mind has been operational since 2017, and has worked on a wide range of projects, including PC and mobile games, virtual and augmented reality applications, and blockchain projects. They have been intricately involved in the development of Decentraland, and have designed multiple in the Metaverse. Some of their other contributions include the Momus Park, the Escape Room and the Aetherian B. Museum. Polygonal Mind projects The Train Transit system ( ) has been developed as a linear track, with stops for users to onboard or deboard between its line start and end. The stations are accessible through an elevator from the ground level. Two wagons going in opposite directions constitute the train, in order to avoid long waiting queues for users. -68, -117 Ground-up view of the Train Transit System The décor of the stations and the trains has been heavily inspired by the popular PC game Bioshock. Each station has two levels of platforms, one placed at 16m and another platform placed on the 32m level. All the platforms are connected to one another such that you can easily turn around in the opposite direction in case you’ve missed your stop by mistake, just like a normal subway design. In the words of Kourtin, one of the artists in the Polygonal Mind team, “I started defining the design of the whole elevator, based on how Bioshock portrayed art-deco steampunk elevators. I decided to follow a similar approach from scratch to the final model visuals. The design came to be open and wall-less in order to avoid a claustrophobic feeling.” Walking up to one of the platforms in the Transit Network The train runs on an arid, vegetation-less landscape with a rocky environment, and the surroundings are detailed with resting areas and pipes decorating the paths. To add finishing touches, a limited number of curated art pieces have been placed along the trail. You can view and admire them on your way to your destination, or as you wait at the station for the train. And these are just a few of the many Decentraland experiences that we could find time to explore in the last few weeks. There’s so much more to do – raise dragons Tamagotchi-style (My Little Dragon), explore island forests (Lemursiv by Eden Projects), throw pick-axes at the Viking Gym, buy merch at Barter Town, and so on. In a few days, you will also be able to play at a massive retro-style arcade being built by Atari. What are some of your favourite things to do in Decentraland? Let Rohit and me know on . Telegram : The authors have no vested interest in any of the projects mentioned in the article. They individually hold tiny amounts of $MANA and $DAI for testing out Decentraland-based projects and other dApps. They don't own any $DG. Disclosure : is an Analog Design Engineer working at Texas Instruments. is a banker-turned-entrepreneur. They are high school friends who lost contact years ago. They reunited over crypto in early 2018 and have been investing through mutual research and shared knowledge. About the authors Rohit Chatterjee Abhijoy Sarkar

Ready Player One on Ethereum? Welcome to Decentraland!

Harnessing AI to evolve solid MtG decks from cards you already own Tell me if this sounds familiar. You’ve got a box (indeed, boxes!) full of Magic: The Gathering cards, nearly all from boosters you either bought because cracking boosters is fun, or (more likely) that you’ve accumulated from limited events. Most are bulk commons, but there’s definitely a few really interesting cards in there — but because they’re singles or doubles, and you don’t really play that color, they’re just gathering dust. You’re thinking: The meta-game needs a bit of a shakeup, but everyone’s so damned focused on and . You’re sure you’ve got something in your collection that can bring an element of surprise, and maybe even a solid win or two. Karn, Scion of Urza Walking Ballista But where to start? is an resource, but it’s core use case doesn’t cover our issue. It’s geared to helping you when you already know what you want, and you already know what you own (and don’t own). Scryfall amazing Wouldn’t it be great if there were a that could pluck interesting and novel card combos from your existing collection? Wouldn’t it be even better if that tool could craft a solid deck around those core cards, that you could start playing with ? tool today Maybe I’m alone in this, but this is certainly how I feel. So I started building just such a tool. Read along to find out how it works, how you can start using it, and better yet, how you can help make it awesome. In this article, I want to outline at a high level how I approached this challenge, how my approach works, what went well, and what didn’t. If you just want to jump directly to the code, or a deep-dive into the technical nitty-gritty for yourself, you . can dig deeper on GitHub In particular, I want to talk about an approach to deck building using a technique called or GAs. GAs allow us to literally good decks using . Ooooooooh! Yes, it as exciting as it sounds! genetic algorithms evolve artificial selection is Spoiler alert: I brought a deck generated by this tool to the February 2018 , and went 0–7, coming in dead last. But I won a couple of games, and surprised almost everyone there, with a deck built around and . It was…interesting. There’s obviously a of work to be done! But it’s been pretty fun so far, and that’s what matters the most to me. Dutch Standard Open Mechanized Production Barricade Breaker lot Genetic Algorithms So, what’s a genetic (GA)? And how can they help us? algorithm The goal of GAs design is to find good enough solutions to optimization problems in a reasonable amount of time. An optimization problem is one in which there are a range of possible solutions — a range too large to search one-by-one, and some solutions are better than others. The classic example is the : Given a set of items of particular size, shape, and weight, and a knapsack to store them in, what’s the best arrangement of them to get as many as possible packed? knapsack problem Deck-building is an optimization problem, too. Given that there are something like 20,000 distinct cards in print, and that we might individually own a collection of several thousand, in multiple copies of many cards, we want to identify the 60 cards from our collection that, as a deck, give us the greatest chance of winning a game of Magic. When we can express the solution to an optimization problem as a sequence of discrete items, like genes in a chromosome, genetic algorithms provide an interesting way to find solutions by them (I’ll discuss how below). And guess what? A decklist just is a sequence of discrete items, making deck building an ideal problem to approach with a GA. good enough evolving Genetic Algorithms The way GAs work is through a process called , quite explicitly modeled after the biological process of evolution by natural selection. As you can guess, the terminology for this algorithm is all borrowed from evolutionary biology. evolution by artificial selection To begin, we randomly generate an initial population of several thousand individual solutions (that is, in our case, decks comprising only cards that I already own). Then, each member of the population is evaluated on their optimality (their “fitness”). Then, individuals are selected from the population in pairs — the greater their fitness, the more likely they are to be selected. Then those two individuals are crossed — the sequences of cards chopped up and recombined — to create new individuals for the next generation. Sometimes, individuals will receive a random mutation, just to keep things fresh. This process is repeated many times, and what comes out of the other end considerably more optimal than the random individuals that started the process. It’s almost… . 🤩 magical But what drives the whole thing, what everything depends upon, is how we evaluate optimality, the . Essentially, we need to tell the GA how good a deck is. For some problems, the fitness function is straightforward. For example, in the knapsack problem, we can ask: How many items did we manage to stuff into the knapsack? But with Magic decks, this question is a harder to answer. fitness function lot The Fitness of a Magic Deck We’re thinking of Magic decks as sequences of cards that can be sliced, diced, and rearranged to make new decks. That’s the easy part. But how do we evaluate whether what we have is a deck? good We’re going to work by assigning points to a deck, depending on how closely it meets a set of rules. Some rules assign points to the deck as a gestalt, and some assign points to individual cards, which are then tallied up. The more points, the better the deck. For my tool, I set some basic assumptions — these are far from universal, but the more constraints on what makes a good deck, the better a GA often performs, especially in a problem space as large as ours. No individual card can appear in the deck twice (because this is physically impossible) and the deck may not contain more than 4 copies of any card (because rules). Such cards are removed from the deck. Decks should consist of exactly N colors, where N defaults to 2, but can be specified. Cards not of the N top colors are removed from the deck. Decks contain 36 non-land cards. (We don’t need the GA wasting cycles adding land to our deck, we can do that ourselves manually at very little mental cost later.) Decks lose points if they are too small — and they be too small if rule 1 or 2 is broken. will Decks should approximate a mana curve of• 9 One-Drops• 13 Two-Drops• 9 Three-Drops• 3 Four-Drops(Borrowed from this on Channel Fireball.) We calculate the euclidean distance from our actual deck to this ideal, and assign points based on how close the deck is to the ideal. excellent analysis Decks should roughly consist of• 16 Creatures• 8 Artifacts• 3 Enchantments• 1 Planeswalker• 3 Instants• 3 Sorceries(Totally made up, and driven by my love of the artifact-heavy .) We again calculate the euclidean distance to this ideal, and assign points based on how close the deck is to the ideal. Kaladesh block The greater the average power and average toughness of the creatures, the better. Better power and better toughness get more points. (At the moment, the GA doesn’t check to see if the deck is legal for any particular format, but that wouldn’t be hard to add.) The idea is that decks don’t have to conform exactly to these criteria, but that we can grade them on how closely they meet each criterion. Granted these constraints are arbitrary (they are totally configurable in the code, of course!), and subject to taste. They’re maybe not even the most important considerations, but they are fundamental, and we can at least demonstrate that the GA is working if the resulting decks have the right number of colors, the specified mana curve, and the specified type distribution. And, in fact, at this point we can demonstrably use a GA to generate decks that meet these criteria reasonably closely. These decks will be , and to a certain degree , but they won’t be very , which is a key part of our problem. legal playable interesting To wit, here’s an example deck built with only these constraints in the fitness function: . As you can see, it meets all the stipulated requirements: It has a solid mana curve, it’s got a reasonable distribution of card types, it’s (mostly) legal. It’s playable. And of course it consists of cards that I already own. That’s pretty amazing considering the GA began by just randomly selecting 36 cards! But it’s far from great. An Evolved Pile of Cards Almost the definition of a pile of cards. But at least it’s Standard legal? Just pretend you didn’t see that Attune with Aether. https://deckstats.net/decks/108990/1006014-an-evolved-pile-of-cards Two observations: Interestingly, at this point, most decks produced are Red/Green, probably because of rule number 5 above (maximize average power and toughness). Also, most of the creatures are further up the curve, for undoubtedly the same reason, leaving in instants, sorceries, enchantments and artifacts to take up the 1-drop and 2-drop slots. Clearly this is far from optimal. Of course there is absolutely no synergy among the cards. Let’s do something about that. Yawn. Card abilities and interactions So, the obvious next step, assuming we don’t find the prior assumptions about good decks horribly offensive (we can tweak them later, at least we know they are working), is to tell the fitness function something about how cards interact with each other. At this stage, I tried to describe my cards in a way that I could use in the fitness function. I hand-tagged each of my cards (trying my best to use community jargon, but often as not failing no doubt) with the various abilities they have: For example, flying or card drawing. For example, I tagged as “granting hex proof” and “granting indestructible”. Heroic Intervention I also hand-tagged each of my cards based on the triggers for triggered abilities, for example, enters-the-battlefield, or…well, actually, that’s as far as I got, because the range of possible triggers is rather overwhelming. For example, I tagged as having an enters-the-battlefield trigger. Felidar Guardian I then hand-tagged each of my cards if they have an interesting interaction with cards with specific abilities, triggers, or card types. I called these (a mistake!) “affinities”. For example, has an affinity for artifacts. Embraal Gear-Smasher You can find all of these annotations in in the code. There’s a lot going on there! data/annotations.json Then, I also created a list of more general interactions — both positive and negative. For example, flying creatures (to my mind!) get a little bit better when there are more of them, but they don’t pair well with cards that grant flying (because that’s redundant). Cards that produce energy (this is Kaladesh, after all!) pair very nicely with cards that consume energy, but don’t interact at all with cards that don’t use the energy mechanic. Creating this list was a thankless task, so I left it quite short, focused on interactions that I was particularly interested in (especially energy!). You can find the list of interactions I documented in . data/interactions.json Then, in the fitness function, I added a few more rules. The fitness function examines each pair of cards in the deck: Card pairs with abilities that interact well are given points. Card pairs that interact negatively lose points. Card pairs where one has an affinity for the other (using my own terminology described above) are given points. Now, for example, when the fitness function sees two flying creatures, it nods in approval. When it sees Embraal Gear-Smasher paired with an artifact, it nods in approval. When it sees paired with , it gets shirty. Aetherstorm Roc Mighty Leap The Results So: A good deck is legal, has a good mana curve and distribution of card types, and is rich in card affinities and interactions. How does the GA perform with this measure of fitness? Have a look at , and see what you think. Evolved Energy More than a pile, less than GP-winning. https://deckstats.net/decks/108990/1006019-evolved-energy Not freaking bad, considering we’re measuring only a small subset of abilities and potential interactions (with a heavy emphasis on energy and enters-the-battle-field effects), and starting from randomly generated decks, and we’re constrained to my rather limited collection! But it could be a hell of a lot better. Clearly, we’re being hamstrung by the rules-based approach of identifying and making explicit each and every ability and interaction. I am pretty sure the next step will involve moving to a more statistically-oriented system, rather than trying to make very possible interaction explicit. If you want to give it a spin for yourself, the code is open source and . The README contains building and running instructions. available on GitHub Future Work The mechanism for tracking abilities, interactions, and so forth is incredibly cumbersome. For one thing, it requires on manually curating card. For another, I don’t think my system of labeling abilities is especially good. It’s also needlessly complex. each Better would be a system that looked at what successful decks actually look like in the wild, and generalizing from what’s worked for others. What could that look like? The next step, as I see it, is twofold. First, I want to deploy some natural language processing techniques like to build a set of card archetypes, based on the rules text s— I’ve already started on this and am seeing some promising early results that I hope to share soon. this fun experiment with deck archetypes But the card tags won’t be helpful by themselves. So the second step is to start pulling down top-tier deck lists, and examining how the card archetypes generated in the previous step interact with each other in the wild. From this, we can build a statistical model that we can feed into the fitness function. We can ask: Here is a card, what are its archetypes? Do these archetypes hang together with the other archetypes seen in the deck, based on what we’ve seen in the wild? This is, I think, where this project is heading. I’ll have a new progress report soon! How You Can Help I would love some help with this. Let’s be honest, though: The code is a mess. Basically, I just threw code together until it worked, with only a modicum of sensible code structure and commentary. It’s not very clear exactly how the code goes about its business. That’s on me. But if you really do want to jump in, and you’re willing to be patient with me as I document things, well, just start digging in on anything you see that’s missing that you can fix. The codebase and structure could be cleaner, it could be more user friendly. Just have a look at the around the project. GitHub issues I’ll be opening up additional projects in the near future for building card archetypes, as well as analyzing the archetypes of successful decks, if you’re interested in helping push that forward. And if you just want to show your appreciation, you can always use my when shopping for your next deck, or just hit the applaud button below! Cardmarket affiliate link

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