Authors:
(1) Avrim Blum, Toyota Technological Institute at Chicago, IL, USA;
(2) Melissa Dutz, Toyota Technological Institute at Chicago, IL, USA.
Table of Links
2 Setting and 2.1 Models of behaviorally-biased opponents
4.1 Myopic Best Responder and 4.2 Gamblerโs Fallacy Opponent
4.3 Win-Stay, Lose-Shift Opponent
4.4 Follow-the-Leader Opponent and 4.5 Highest Average Payoff Opponent
5 Generalizing
5.1 Other Behaviorally-Biased Strategies
5.2 Exploiting an Unknown Strategy from a Known Set of Strategies
A Appendix
A.1 Win-Stay Lose-Shift Variant: Tie-Stay
A.2 Follow-the-Leader Variant: Limited History
A.4 Highest Average Payoff Opponent
A.3 Ellipsoid Mistake Bounds
Follow-the-Leader Opponent
Highest Average Payoff Opponent
This paper is available on arxiv under CC BY 4.0 DEED license.
