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arXiv:1905.06602math.OC

Emergence of Exploitation as Symmetry Breaking in Iterated Prisoner's Dilemma

Yuma Fujimoto, Kunihiko Kaneko

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Abstract

In society, mutual cooperation, defection, and asymmetric exploitative relationships are common. Whereas cooperation and defection are studied extensively in the literature on game theory, asymmetric exploitative relationships between players are little explored. In a recent study, Press and Dyson demonstrate that if only one player can learn about the other, asymmetric exploitation is achieved in the prisoner's dilemma game. In contrast, however, it is unknown whether such one-way exploitation is stably established when both players learn about each other symmetrically and try to optimize their payoffs. Here, we first formulate a dynamical system that describes the change in a player's probabilistic strategy with reinforcement learning to obtain greater payoffs, based on the recognition of the other player. By applying this formulation to the standard prisoner's dilemma game, we numerically and analytically demonstrate that an exploitative relationship can be achieved despite symmetric strategy dynamics and symmetric rule of games. This exploitative relationship is stable, even though the exploited player, who receives a lower payoff than the exploiting player, has optimized the own strategy. Whether the final equilibrium state is mutual cooperation, defection, or exploitation, crucially depends on the initial conditions: Punishment against a defector oscillates between the players, and thus a complicated basin structure to the final equilibrium appears. In other words, slight differences in the initial state may lead to drastic changes in the final state. Considering the generality of the result, this study provides a new perspective on the origin of exploitation in society.

arXiv comments
19 pages, 7 figures, + supplement(8 pages, 2 figures)
Journal reference
Phys. Rev. Research 1, 033077 (2019)
DOI
doi:10.1103/PhysRevResearch.1.033077
Subjects
math.OCOptimization and Control nlin.AOAdaptation and Self-Organizing Systems physics.soc-phPhysics and Society

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