Assessing the Utilization of Automata in Representing Players' Behaviors in Game Theory

Abstract

Representing players' strategies in game theory has a direct impact on the players' performance. The state of art shows that automata are one of the primary techniques used for representing players' strategies and behaviors. In this paper, the author will identify different types of automata and assess their utilization in the field of game theory. Is has been found that finite automata, adaptive automata, and cellular automata are widely adopted in game theory. The utilization of finite automata is found to be limited to represent simpler players' behavior. On the other hand, adaptive automata and cellular automata are intensively applied in complex environments, where the number of interacted players is large and therefore, representing complex behaviors are needed.

Conditions that enable a player to surely win in sequential quantum games

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