Ellipsoid Algorithms as a Tool Against Predictable Opponents Post date January 24, 2025 Post author By Algorithmic Bias Post categories In behavioral-biases, best-response-learning, ellipsoid-algorithm, follow-the-leader, limited-history-variant, payoff-matrix-approximation, predictive-strategies, zero-sum-games
Understanding Bias-Driven Opponent Models in Competitive Gameplay Post date January 24, 2025 Post author By Algorithmic Bias Post categories In behavioral-biases, gambler's-fallacy, game-theory, myopic-best-responder, reinforcement-learning, symmetric-games, win-stay-lose-shift, zero-sum-games
Ways to Counter Limited-History Opponents with Algorithmic Tools Post date January 24, 2025 Post author By Algorithmic Bias Post categories In behavioral-biases, best-response-learning, ellipsoid-algorithm, follow-the-leader, limited-history-variant, permissible-games, predictive-strategy, zero-sum-games
Future Directions for Exploiting Behavioral Biases in Games Post date January 24, 2025 Post author By Algorithmic Bias Post categories In behavioral-biases, exploitability, extensive-form-games, future-research, probabilistic-strategies, regret-minimization, strategy-performance, zero-sum-games
Broader Insights into Exploitable Strategies in Zero-Sum Games Post date January 24, 2025 Post author By Algorithmic Bias Post categories In behavioral-biases, best-response-learning, deterministic-strategies, exploiting-biases, halving-algorithm, predicting-actions, strategy-generalization, zero-sum-games
How Behavioral Biases Shape Gameplay Without Payoff Visibility Post date January 24, 2025 Post author By Algorithmic Bias Post categories In behavioral-bias, competitive-gaming, copycat-algorithm, exploiting-strategies, game-theory, opponent-prediction, symmetric-games, zero-sum-games
Methods for Decoding Opponent Actions and Optimizing Responses Post date January 24, 2025 Post author By Algorithmic Bias Post categories In behavioral-biases, best-responses, game-matrices, game-theory, halving-algorithm, myopic-best-responder, predicting-opponents, zero-sum-games
The Key to Defeating Win-Stay, Lose-Shift Opponent Variants Post date January 24, 2025 Post author By Algorithmic Bias Post categories In action-ordering, behavioral-biases, best-response-algorithms, game-theory, strategy-exploitation, tie-shift-variant, tie-stay-variant, win-stay-lose-shift
Strategies to Exploit Myopic and Gambler’s Fallacy Opponents Post date January 24, 2025 Post author By Algorithmic Bias Post categories In behavioral-biases, best-responses, gambler's-fallacy, game-theory, myopic-best-responder, permissible-games, predictive-algorithms, zero-sum-games
Algorithm 8’s Approach to Countering the Highest Average Payoff Opponent Post date January 24, 2025 Post author By Algorithmic Bias Post categories In behavioral-bias, behavioral-strategies, best-response-learning, ellipsoid-algorithm, game-matrix-approximation, highest-average-payoff, predictive-algorithms, zero-sum-games
A Guide to Exploiting Unknown Strategies From a Known Bias Set Post date January 24, 2025 Post author By Algorithmic Bias Post categories In behavioral-biases, best-response-learning, halving-algorithm, prediction-algorithms, strategy-exploitation, strategy-sets, unknown-strategies, zero-sum-games
Techniques to Beat the Tie-Stay Variant of Win-Stay, Lose-Shift Post date January 24, 2025 Post author By Algorithmic Bias Post categories In action-order-prediction, algorithm-6, behavioral-strategies, best-response-learning, permissible-games, tie-stay-variant, win-stay-lose-shift, zero-sum-games
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