2014/04/21 by Zhijian Wang, Bin Xu, Hai-Jun Zhou · 95 citations
Computer Science · Economics, Econometrics and Finance · Physics and Astronomy · Social Sciences · #Action (physics) #Bounded rationality #Competition (biology) #Complex Systems and Time Series Analysis #Evolutionary Game Theory and Cooperation #Evolutionary game theory #Game theory #Iterated function #Nash equilibrium #Normal-form game #Opinion Dynamics and Social Influence #Repeated game #Stochastic game #cs.GT #physics.soc-ph
paper · pdf · doi:10.1038/srep05830
published in Scientific Reports 4(1), 5830 (Nature Portfolio) · 7 pages + 14 pages supplementary information
arxiv created 2014/04/21 · openalex publication_date 2014/07/25 · arxiv updated 2014/07/29 · openalex created_date 2016/06/24 · openalex updated_date 2026/08/05
How humans make decisions in non-cooperative strategic interactions is a big question. For the fundamental Rock-Paper-Scissors (RPS) model game system, classic Nash equilibrium (NE) theory predicts that players randomize completely their action choices to avoid being exploited, while evolutionary game theory of bounded rationality in general predicts persistent cyclic motions, especially in finite populations. However as empirical studies have been relatively sparse, it is still a controversial issue as to which theoretical framework is more appropriate to describe decision-making of human subjects. Here we observe population-level persistent cyclic motions in a laboratory experiment of the discrete-time iterated RPS game under the traditional random pairwise-matching protocol. This collective behavior contradicts with the NE theory but is quantitatively explained, without any adjustable parameter, by a microscopic model of win-lose-tie conditional response. Theoretical calculations suggest that if all players adopt the same optimized conditional response strategy, their accumulated payoff will be much higher than the reference value of the NE mixed strategy. Our work demonstrates the feasibility of understanding human competition behaviors from the angle of non-equilibrium statistical physics.