Equilibrium state and non-equilibrium steady state in an isolated human system

Zheng, Wenzhi; Liang, Yuan; Huang, Jiping

doi:10.1007/s11467-013-0337-5

Cited by 4 publications

(8 citation statements)

References 22 publications

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“…Human experiment results have been used to improve or change the system of study or understand the effect of changes in the system circumstances based on the human behavior results. [46][47][48][49] Also, ABM has been used to support human subject experiment results or can be used as the system of study when using human subject experiment is not appropriate. 48,[50][51][52] When discussing ABM, we would like to highlight another agent-based oriented model called multi-agent system (MAS) that is sometimes confused with ABM.…”

Section: Abmmentioning

confidence: 99%

Computerized agents versus human agents in finding core coalition in glove games

2022

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One of the challenges for agent-based modeling is being able to incorporate human behavior. Human behavior is a multifaceted phenomenon, with strategic coalition formation being one form. A hybrid agent-based modeling approach, called ABMSCORE, has been derived to emulate strategic group formation. In this paper, we describe a simulation experiment to compare the ABMSCORE with actual human behavior. The comparison criterion is the respective rates of finding an ideal coalition. In our experimental design, we go to great lengths to ensure the similarity of the scenarios in the two trial types: trials with computerized agents only and trials involving human participants when one of the computerized agents is replaced by an actual human. We did this to limit the number of possible extraneous variables introduced into the experimental system. The scenario considered is the glove game, a standard cooperative game that has been previously used in human experiments. Our results indicate that the ABMSCORE model produces similar rates of finding the ideal coalition as the human players; however, there are some limitations. This research provides evidence for using the ABMSCORE modeling approach to model human strategic coalition formation in agent-based models.

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Section: Abmmentioning

confidence: 99%

Computerized agents versus human agents in finding core coalition in glove games

2022

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“…To measure the degree of uncertainty associated with the macroscopic arbitrage opportunities in our human system, we follow the definition of Shannon entropy in the information theory, and define the entropy-like quantity (s), [54,67] a state function of our system, as…”

Section: Entropy-like Quantity Describing the Degree Of Uncertaintymentioning

confidence: 99%

“…They have also experimentally investigated the social human system with the clustering effect and revealed the trend of the entropy-like quantity based on the MDRAG. [54] For our purpose, the clustering effect is described by defining a probability, q (0 ≤ q ≤ 1), for each human to get to know the others. The increase of q can characterize the degree of the clustering effect.…”

Section: Non-equilibrium Steady Statementioning

confidence: 99%

“…The horizontal dashed lines denote the equilibrium state with the maximum entropy of s = 0.693. [54] Now let us turn to the DOP displayed in Fig. 26.…”

Section: Non-equilibrium Steady Statementioning

confidence: 99%

“…[51,53] Then we survey a few human counterparts of some laws or phenomena of the traditional statistical physics under some conditions, namely, two-phase phenomena or phase transitions (Section 4.1), [50,51,53] entropyrelated phenomena (Section 4.2), [51,67] and non-equilibrium steady state (Section 4.3). [54] This review ends with a summary and outlook in Section 5.…”

Section: Introductionmentioning

confidence: 99%

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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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Chaotic-periodic transition in a two-sided minority game

Yang

Huang

2016

Front. Phys.

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Equilibrium state and non-equilibrium steady state in an isolated human system

Cited by 4 publications

References 22 publications

Computerized agents versus human agents in finding core coalition in glove games

Computerized agents versus human agents in finding core coalition in glove games

Statistical physics of human beings in games: Controlled experiments

Chaotic-periodic transition in a two-sided minority game

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