We propose a simple uncertainty modification for the agent model in normal-form games; at any given strategy profile, the agent can access only a set of “possible profiles” that are within a certain distance from the actual action profile. We investigate the various instantiations in which the agent chooses her strategy using well-known rationales e.g., considering the worst case, or trying to minimize the regret, to cope with such uncertainty. Any such modification in the behavioral model naturally induces a corresponding notion of equilibrium; a distance-based equilibrium. We characterize the relationships between the various equilibria, and also their connections to well-known existing solution concepts such as Trembling-hand perfection. Furthermore, we deliver existence results, and show that for some class of games, such solution concepts can actually lead to better outcomes.
CITATION STYLE
Acar, E., & Meir, R. (2020). Distance-based equilibria in normal-form games. In AAAI 2020 - 34th AAAI Conference on Artificial Intelligence (pp. 1750–1757). AAAI press. https://doi.org/10.1609/aaai.v34i02.5540
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