Functional dynamic by intention recognition in iterated games

Fujimoto, Yuma; Kaneko, Kunihiko

doi:10.1088/1367-2630/ab0459

Cited by 4 publications

(4 citation statements)

References 43 publications

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“…holds. Since f x is player 1's probability of cooperating given player 2's probability of cooperating, we call it the "response function", following the previous studies [15].…”

Section: Intuitive Interpretation Of the Modelmentioning

confidence: 99%

“…7, 8, and 10) seem complicated at first glance. However, we can intuitively interpret them by employing the concept of the response function [15].…”

Section: Intuitive Interpretation Of the Modelmentioning

confidence: 99%

“…Indeed, against player y = 1 (i.e., a pure cooperator), f x (1) = x C holds, whereas, against a pure defector, f x (0) = x D holds. Since f x is player 1's probability of cooperating given player 2's probability of cooperating, we call it the "response function", following the previous studies [15].…”

Section: Intuitive Interpretation Of the Modelmentioning

confidence: 99%

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Emergence of exploitation as symmetry breaking in iterated prisoner's dilemma

Fujimoto

Kaneko

2019

Phys. Rev. Research

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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 [1] 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.

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“…holds. Since f x is player 1's probability of cooperating given player 2's probability of cooperating, we call it the "response function", following the previous studies [15].…”

Section: Intuitive Interpretation Of the Modelmentioning

confidence: 99%

“…7, 8, and 10) seem complicated at first glance. However, we can intuitively interpret them by employing the concept of the response function [15].…”

Section: Intuitive Interpretation Of the Modelmentioning

confidence: 99%

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Emergence of exploitation as symmetry breaking in iterated prisoner's dilemma

Fujimoto

Kaneko

2019

Phys. Rev. Research

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“…Thus, a player with more detailed information about a previous round has a higher ability to choose their own optimal action. This ability to observe actions of their own and their opponents is seen in reality, such as intention recognition [2][3][4][5][6][7][8]. Furthermore, in social systems, from the bacterial community to international war, the reference to past actions might play an important role in establishing interpersonal relationships [9].…”

Section: Introductionmentioning

confidence: 99%

Exploitation by asymmetry of information reference in coevolutionary learning in prisoner's dilemma game

Fujimoto¹,

Kaneko²

2021

Preprint

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Mutual relationships, such as cooperation and exploitation, are the basis of human and other biological societies. The foundations of these relationships are rooted in the decision making of individuals, and whether they choose to be selfish or altruistic. How individuals choose their behaviors can be analyzed using a strategy optimization process in the framework of game theory. Previous studies have shown that reference to individuals' previous actions plays an important role in their choice of strategies and establishment of social relationships. A fundamental question remains as to whether an individual with more information can exploit another who has less information when learning the choice of strategies.Here we demonstrate that a player using a memory-one strategy, who can refer to their own previous action and that of their opponent, can be exploited by a reactive player, who only has the information of the other player, based on mutual adaptive learning. This is counterintuitive because the former has more choice in strategies and can potentially obtain a higher payoff. We demonstrated this by formulating the learning process of strategy choices to optimize the payoffs in terms of coupled replicator dynamics and applying it to the prisoner's dilemma game. Further, we show that the player using a memory-one strategy, by referring to their previous experience, can sometimes act more generous toward the opponent's defection, thereby accepting the opponent's exploitation. Mainly, we found that through adaptive learning, a player with limited information usually exploits the player with more information, leading to asymmetric exploitation.

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Leadership scenarios in prisoner’s dilemma game

Babajanyan

Melkikh

Allahverdyan

2020

Physica A: Statistical Mechanics and its Applications

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The prisoner's dilemma game is the most known contribution of game theory into social sciences. Here we describe new implications of this game for transactional and transformative leadership. While the autocratic (Stackelberg's) leadership is inefficient for this game, we discuss a Paretooptimal scenario, where the leader L commits to react probabilistically to pure strategies of the follower F, which is free to make the first move. Offering F to resolve the dilemma, L is able to get a larger average pay-off. The exploitation can be stabilized via repeated interaction of L and F, and turns to be more stable than the egalitarian regime, where the pay-offs of L and F are equal. The total (summary) pay-off of the exploiting regime is never larger than in the egalitarian case. We discuss applications of this solution to a soft method of fighting corruption and to modeling the Machiavellian leadership. Whenever the defection benefit is large, the optimal strategies of F are mixed, while the summary pay-off is maximal. One mechanism for sustaining this solution is that L recognizes intentions of F.

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Functional dynamic by intention recognition in iterated games

Cited by 4 publications

References 43 publications

Emergence of exploitation as symmetry breaking in iterated prisoner's dilemma

Emergence of exploitation as symmetry breaking in iterated prisoner's dilemma

Exploitation by asymmetry of information reference in coevolutionary learning in prisoner's dilemma game

Leadership scenarios in prisoner’s dilemma game

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