Apr 11, 2022 � Abstract:We extend the classic regret minimization framework for approximating equilibria in normal-form games by greedily weighing iterates�...
We extend the classic regret minimization framework for approximating equilibria in normal-form games by greedily weighing iterates based on regrets observed�...
Apr 11, 2022 � Empirically, experiments on large randomly generated games and normal-form subgames of the AI benchmark Diplomacy show that greedy weights�...
Apr 11, 2022 � We extend the classic regret minimization framework for approximating equilibria in normal-form games by greedily weighing iterates based on�...
We extend the classic regret minimization framework for approximating equilibria in normal-form games by greedily weighing iterates based on regrets�...
Nash equilibrium implicitly assumes that the players know what strategy the other players are using. Such knowledge seems unreasonable, especially in one-shot�...
We present a general reduction showing how to convert any algorithm for minimizing external regret to one that minimizes this stronger form of regret as well.
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a Nash equilibrium in zero-sum normal form games and ... Finding optimal abstract strategies in extensive form ... Regret minimization in games with incom- plete�...
It is well- known that regret-minimizing algorithms converge to certain classes of equilibria in games; however, traditional forms of regret used in game theory�...
One efficient method for computing. Nash equilibria in large, zero-sum, imperfect information games is counterfactual regret minimization (CFR). In the domain�...