Fish play Minority Game as humans do

Liu, Ruey-Tarng; Chung, Fei Fang; Liaw, Sy-Sang

doi:10.1209/0295-5075/97/20004

Cited by 5 publications

(2 citation statements)

References 23 publications

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“…(iii) Extending controlled experiments from human beings to other animals like ants [158] or fish [159] could be of value to study statistical physics of other kinds of adaptive agents beyond human beings. By doing so, people could understand those animals more by using concepts or tools originating from the traditional statistical physics.…”

Section: Three Directions For Future Researchmentioning

confidence: 99%

Statistical physics of human beings in games: Controlled experiments

Yuan¹,

Huang²

2014

Chinese Phys. B

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It is important to know whether the laws or phenomena in statistical physics for natural systems with non-adaptive agents still hold for social human systems with adaptive agents, because this implies whether it is possible to study or understand social human systems by using statistical physics originating from natural systems. For this purpose, we review the role of human adaptability in four kinds of specific human behaviors, namely, normal behavior, herd behavior, contrarian behavior, and hedge behavior. The approach is based on controlled experiments in the framework of market-directed resource-allocation games. The role of the controlled experiments could be at least twofold: adopting the real human decision-making process so that the system under consideration could reflect the performance of genuine human beings; making it possible to obtain macroscopic physical properties of a human system by tuning a particular factor of the system, thus directly revealing cause and effect. As a result, both computer simulations and theoretical analyses help to show a few counterparts of some laws or phenomena in statistical physics for social human systems: two-phase phenomena or phase transitions, entropy-related phenomena, and a non-equilibrium steady state. This review highlights the role of human adaptability in these counterparts, and makes it possible to study or understand some particular social human systems by means of statistical physics coming from natural systems.

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Section: Three Directions For Future Researchmentioning

confidence: 99%

Statistical physics of human beings in games: Controlled experiments

Yuan¹,

Huang²

2014

Chinese Phys. B

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“…Chmura et al (2010) conclude that the observed heterogeneity in players' behavior in games where multiple equivalent equilibria are present must be ascribed to the structure of individuals' preferences rather than to their inability to calculate mixed equilibria. Finally, Liu et al (2010) study minority game properties by comparing behavior in the game played by humans and by sh, and discover several behavioral similarities between the two species.…”

Section: Literature Reviewmentioning

confidence: 99%

The Minority Game Unpacked: Coordination and Competition in a Team-Based Experiment

Devetag

Pancotto

Brenner³

2011

SSRN Journal

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In minority games, players in a group must decide at each round which of two available options to choose, knowing that only subjects who picked the minority option obtain a positive reward. Previous experiments on the minority and similar congestion games have shown that players interacting repeatedly are remarkably able to coordinate eciently, despite not conforming to Nash equilibrium behavior. We conduct an experiment on a minority-of-three game in which each player is a team composed by three subjects. Each team can freely discuss its strategies in the game and decisions must be made via a majority rule. Team discussions are recorded and their content analyzed to detect evidence of strategy co-evolution among teams Philipps University Marburg, Germany 1 playing together. Our main results of team discussion analysis show no evidence supporting the mixed strategy Nash equilibrium solution, and support a low-rationality, backward-looking approach to model behavior in the game, more consistent with reinforcement learning models than with belief-based models. Showing level-2 rationality (i.e., reasoning about others' beliefs) is positively and signicantly correlated with higher than average earnings in the game, showing that a mildly sophisticated approach pays o. In addition, teams that are more successful tend to become more egocentric over time, paying more attention to their own past successes than to the behavior of other teams. Finally, we nd evidence of mutual adaptation over time, as teams that are more strategic (i.e., they pay more attention to other teams' moves)induce competing teams to be more egocentric instead. Our results contribute to the understanding of coordination dynamics resting on heterogeneity and co-evolution of decision rules rather than on conformity to equilibrium behavior. In addition, they provide support at the decision process level to the validity of modeling behavior using low-rationality reinforcement learning models.JEL codes: C72, C91, C92

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