caa a22 4500 606232907 CHVBK 20210128101229.0 cr unu---uuuuu 210128e20150101xx s 000 0 eng 10.1007/s10287-014-0202-1 doi (NATIONALLICENCE)springer-10.1007/s10287-014-0202-1 The evolution of cooperation with different fitness functions using probabilistic cellular automata [Elektronische Daten] [P. Schimit, B. Santos, C. Soares] 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. Springer-Verlag Berlin Heidelberg, 2014 Cellular automata nationallicence Evolution of cooperation nationallicence Game theory nationallicence Hawk-dove nationallicence Prisoner's dilemma nationallicence Schimit P. Universidade Nove de Julho, São Paulo, Brazil aut Santos B. Universidade Nove de Julho, São Paulo, Brazil aut Soares C. Universidade Nove de Julho, São Paulo, Brazil aut Computational Management Science Springer Berlin Heidelberg 12/1(2015-01-01), 35-43 1619-697X 12:1<35 2015 12 10287 https://doi.org/10.1007/s10287-014-0202-1 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s10287-014-0202-1 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Schimit P. Universidade Nove de Julho, São Paulo, Brazil aut NATIONALLICENCE 700 1- Santos B. Universidade Nove de Julho, São Paulo, Brazil aut NATIONALLICENCE 700 1- Soares C. Universidade Nove de Julho, São Paulo, Brazil aut NATIONALLICENCE 773 0- Computational Management Science Springer Berlin Heidelberg 12/1(2015-01-01), 35-43 1619-697X 12:1<35 2015 12 10287