Test MaxEnt in social strategy transitions with experimental two-person constant sum 2 × 2 games

Chen

Physica A: Statistical Mechanics and its Applications

2017

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Understanding the dynamic processes of a real game system requires an appropriate dynamics model, and rigorously testing a dynamics model is nontrivial. In our methodological research, we develop an approach to testing the validity of game dynamics models that considers the dynamic patterns of angular momentum and speed as measurement variables. Using Rock-PaperScissors (RPS) games as an example, we illustrate the geometric patterns in the experiment data. We then derive the related theoretical patterns from a series of typical dynamics models. By testing the goodness-of-fit between the experimental and theoretical patterns, we show that the validity of these models can be evaluated quantitatively. Our approach establishes a link between dynamics models and experimental systems, which is, to the best of our knowledge, the most effective and rigorous strategy for ascertaining the testability of evolutionary game dynamics models.

Section: Logic Of Our Approachmentioning

confidence: 99%

Testability of evolutionary game dynamics based on experimental economics data

Chen

Physica A: Statistical Mechanics and its Applications

2017

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“…For example, the social state 3 denoted as x A =( 2 4 , 1 4 ) is a state where 2 4 of subjects in the first population choose X 1 and 1 4 of subjects in the second population choose Y 1 . It is clear that, at a given round (time) in an experiment, the social state can be observed [22,37,25,18].…”

Section: A1 Social Statesmentioning

confidence: 99%

Periodic frequencies of the cycles in 2 × 2 games: evidence from experimental economics

2014

Eur. Phys. J. B

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Abstract. Evolutionary dynamics provides an iconic relationship-the periodic frequency of a game is determined by the payoff matrix of the game. This paper reports the first experimental evidence to demonstrate this relationship. Evidence comes from two populations randomly-matched 2 × 2 games with 12 different payoff matrix parameters. The directions, frequencies and changes in the radius of the cycles are measured definitively. The main finding is that the observed periodic frequencies of the persistent cycles are significantly different in games with different parameters. Two replicator dynamics, standard and adjusted, are employed as predictors for the periodic frequency. Interestingly, both of the models could infer the difference of the observed frequencies well. The experimental frequencies linearly, positively and significantly relate to the theoretical frequencies, but the adjusted model performs slightly better.

“…Two of the present authors partially overcame these difficulties by using social state velocity vectors26 and forward and backward transition vectors27 to visualize violation of detailed balance in game evolution trajectories, but a simple way of quantitatively measuring persistent cyclic behavoiors in a highly stochastic trajectory was still lacking. The cycling frequency of directional flows in the neutral RPS game ( a = 2) was later quantitatively measured in28 using a coarse-grained counting technique.…”

mentioning

confidence: 99%

Social cycling and conditional responses in the Rock-Paper-Scissors game

Zhou

2014

Sci Rep

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121

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.