The article discusses various models of behaviorally-biased opponents in strategic games. It emphasizes understanding different decision-making strategies like Myopic Best Responder and Gambler's Fallacy. A significant focus is on the Follow-the-Leader opponent, particularly the limited-history variant, which considers past interactions to adjust future actions. This dynamic highlights the importance of adapting strategies in response to an opponent's behavior, suggesting a necessity for strategic flexibility to exploit biases effectively in uncertain environments. Additionally, the ellipsoid algorithm is utilized for prediction purposes, showcasing its application in these situational models.
The limited-history variant of the Follow-the-Leader opponent plays the action that would have achieved the highest net payoff against the last r rounds of our play.
If r = 0, the opponent would simply play the same action every round, resulting in tied outcomes unless adaptive strategies are deployed.
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