Crossover and Evolutionary Stability in the Prisoner's Dilemma
Evolutionary Computation
Examining the Effect of Elitism in Cellular Genetic Algorithms Using Two Neighborhood Structures
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
Use of Local Ranking in Cellular Genetic Algorithms with Two Neighborhood Structures
SEAL '08 Proceedings of the 7th International Conference on Simulated Evolution and Learning
A strategy with novel evolutionary features for the iterated prisoner's dilemma
Evolutionary Computation
Evolution and incremental learning in the iterated prisoner's dilemma
IEEE Transactions on Evolutionary Computation
Optimal strategies of the iterated prisoner's dilemma problem for multiple conflicting objectives
IEEE Transactions on Evolutionary Computation
IDEAL'07 Proceedings of the 8th international conference on Intelligent data engineering and automated learning
KES-AMSTA'10 Proceedings of the 4th KES international conference on Agent and multi-agent systems: technologies and applications, Part II
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
| Hi-index | 0.00 |
We discuss the evolution of strategies in a spatial iterated prisoner's dilemma (IPD) game in which each player is located in a cell of a two-dimensional grid-world. Following the concept of structured demes, two neighborhood structures are used. One is for the interaction among players through the IPD game. A player in each cell plays against its neighbors defined by this neighborhood structure. The other is for mating strategies by genetic operations. A new strategy for a player is generated by genetic operations from a pair of parent strings, which are selected from its neighboring cells defined by the second neighborhood structure. After examining the effect of the two neighborhood structures on the evolution of cooperative behavior with standard pairing in game-playing, we introduce a random pairing scheme in which each player plays against a different randomly chosen neighbor at every round (i.e., every iteration) of the game. Through computer simulations, we demonstrate that small neighborhood structures facilitate the evolution of cooperative behavior under random pairing in game-playing.