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Algebraization and Optimization of Networked Evolutionary Boxed Pig Games with Passive Reward and Punishment
Author(s) -
Wang Jianjun,
Zhao Jianli,
Fu Shihua
Publication year - 2019
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.1837
Subject(s) - punishment (psychology) , mechanism (biology) , computer science , evolutionary dynamics , mathematical economics , mathematical optimization , control theory (sociology) , psychology , artificial intelligence , mathematics , social psychology , sociology , control (management) , physics , population , demography , quantum mechanics
This paper investigates the evolutionary dynamics and optimization problem of the boxed pig games with the mechanism of passive reward and punishment by using the semi‐tensor product method. First, an algorithm is provided to construct the algebraic formulation for the dynamics of the networked evolutionary boxed pig games with the mechanism of passive reward and punishment. Then, the impact of reward and punishment parameters on the final cooperation level of the whole network is discussed. Finally, an example is provided to show the effectiveness of our results.