Evolutionary Game Theory Based Cooperation Algorithm in Multi-Agent System

Multi-Agent System for task allocation problem, the introduction of game theory for dynamic task allocation modeling Multi-Agent Systems,Multi-Agent System proposed dynamic task allocation algorithm based on game theory.Experimental results show that the lower complexity of dynamic task allocation algorithm based on game theory in this article, the smaller amount of calculation,better robustness,task allocation scheme to obtain higher quality,with higher distribution

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Dynamic Model of Collaboration in Multi-Agent System Based on Evolutionary Game Theory

Games ◽

10.3390/g12040075 ◽

2021 ◽

Vol 12 (4) ◽

pp. 75

Author(s):

Zhuozhuo Gou ◽

Yansong Deng

Keyword(s):

Game Theory ◽

Evolutionary Game Theory ◽

Evolutionary Game ◽

Multi Agent Systems ◽

Exchange Of Information ◽

Message Communication ◽

Stable Conditions ◽

Agent Collaboration ◽

Multi Agent ◽

Reducing Costs

Multi-agent collaboration is greatly important in order to reduce the frequency of errors in message communication and enhance the consistency of exchanging information. This study explores the process of evolutionary decision and stable strategies among multi-agent systems, including followers, leaders, and loners, involved in collaboration based on evolutionary game theory (EGT). The main elements that affected the strategies are discussed, and a 3D evolution model is established. The evolutionary stability strategy (ESS) and stable conditions were analyzed subsequently. Numerical simulation results were obtained through MATLAB simulation, and they manifested that leaders play an important role in exchanging information with other agents, accepting agents’ state information, and sending messages to agents. Then, with the positivity of receiving and feeding back messages for followers, implementing message communication is profitable for the system, and the high positivity can accelerate the exchange of information. At the behavior level, reducing costs can strengthen the punishment of impeding the exchange of information and improve the positivity of collaboration to facilitate the evolutionary convergence toward the ideal state. Finally, the EGT results revealed that the possibility of collaboration between loners and others is improved, and the rewards are increased, thereby promoting the implementation of message communication that encourages leaders to send all messages, improve the feedback positivity of followers, and reduce the hindering degree of loners.

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Modelling on Infectious Disease with Voluntary Vaccination Behavior on Social Networks by Evolutionary Game Theory and Multi-Agent Simulation

JAPANESE JOURNAL OF MULTIPHASE FLOW ◽

10.3811/jjmf.28.280 ◽

2014 ◽

Vol 28 (3) ◽

pp. 280-287

Author(s):

Jun TANIMOTO

Keyword(s):

Infectious Disease ◽

Game Theory ◽

Social Networks ◽

Evolutionary Game Theory ◽

Evolutionary Game ◽

Vaccination Behavior ◽

Agent Simulation ◽

Multi Agent ◽

Voluntary Vaccination

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PATENTING OR SECRET? THE INTERACTION BETWEEN LEADING FIRMS AND FOLLOWING FIRMS BASED ON EVOLUTIONARY GAME THEORY AND MULTI-AGENT SIMULATION

International Journal of Innovation Management ◽

10.1142/s1363919619500683 ◽

2019 ◽

Vol 23 (07) ◽

pp. 1950068 ◽

Cited By ~ 1

Author(s):

XIAOYANG ZHAO

Keyword(s):

Game Theory ◽

Bounded Rationality ◽

Evolutionary Game Theory ◽

Patent Protection ◽

Evolutionary Game ◽

Equilibrium Solutions ◽

Strategic Choices ◽

Trade Off ◽

Multi Agent ◽

Imitation Strategy

Firms who want to appropriate innovation often need to make decision facing the trade-off between patenting and secret. This paper explores how leading firms make trade-off between patenting and secret through the view of the interaction between leading firms and following firms who have the option of imitation or substitution, based on the evolutionary game theory. Then, a simulation model is built combining the evolutionary game model and agent-based modelling method, which allows us to implement bounded rationality and interactivities. The simulation is run with different gain parameters and the results are checked by cross-validation. It is found that leading firms are more likely to adopt patenting strategy with well developed patent protection regime. While depending on variations on patent protection effectiveness, technological characteristics, and leading firms’ investment in patent portfolio development, following firms may choose imitation strategy or substitution strategy. Considering bounded rationality, firms could choose sub-optional strategies and leads to scenarios other than evolutionary equilibrium solutions, which provide deeper insights of strategic choices of leading firms and following firms. This paper makes contributions to theory by using the perspective of multi-agent view and integrating bounded rationality in the simulation. Finally, this paper draws conclusion and puts forward some suggestions.

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