On exploring the genetic algorithm for modeling the evolution of cooperation in a population
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Publication:2300196
DOI10.1016/j.cnsns.2013.12.020OpenAlexW1990769038MaRDI QIDQ2300196
Publication date: 27 February 2020
Published in: Communications in Nonlinear Science and Numerical Simulation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.cnsns.2013.12.020
Computer science (68-XX) Game theory, economics, finance, and other social and behavioral sciences (91-XX)
Related Items (3)
Evolution of cooperation in Axelrod tournament using cellular automata ⋮ The hawk-dove game in phenotypically homogeneous and heterogeneous populations of finite dimension ⋮ Evolutionary aspects of spatial prisoner's dilemma in a population modeled by continuous probabilistic cellular automata and genetic algorithm.
Cites Work
- Evolving cooperation
- Equilibrium selection under evolutionary game dynamics with optimizing behavior
- Infection and immunization: a new class of evolutionary game dynamics
- Evolutionary dynamics of a system with periodic coefficients
- The evolution of cooperation through imitation
- Nonlinear oscillations, dynamical systems, and bifurcations of vector fields
- Cooperation enhanced by the `survival of the fittest' rule in prisoner's dilemma games on complex networks
- Spatial prisoner's dilemma optimally played in small-world networks
- Effects of neighbourhood size and connectivity on the spatial continuous prisoner's dilemma
- Evolutionary prisoner's dilemma in random graphs
- The Evolution of Cooperation
- Collective dynamics of ‘small-world’ networks
- Genetic algorithm learning and evolutionary games
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