The evolution of cooperation with different fitness functions using probabilistic cellular automata

P. Schimit (), B. Santos () and C. Soares ()

Computational Management Science, 2015, vol. 12, issue 1, 35-43

Abstract: In this work, we use probabilistic cellular automata to model a population in which the cells represent individuals that interact with their neighbors playing a game. The games may have either the form of Prisoner’s Dilemma or Hawk-Dove (Snow-Drift, Chicken) games, and may be considered as a competition for a benefit or resource. The result of each game gives each player a payoff, which is decreased from his amount of life. The advantage of such approach is that each player plays with different individuals separately, not as a multi-player matrix game. The probability for an individual having a certain action is considered his strategy, and each action returns a payoff to individual. The purpose of the work is test different fitness functions for evaluating the generation of new individuals, which will have characters of the best adapted individuals in a neighborhood, i.e., have higher values in a fitness function. Copyright Springer-Verlag Berlin Heidelberg 2015

Keywords: Cellular automata; Evolution of cooperation; Game theory; Hawk-dove; Prisoner’s dilemma (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1007/s10287-014-0202-1

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