Cheating for problem solving: a genetic algorithm with social interactions
We propose a variation of the standard genetic algorithm that incorporates social interaction between the individuals in the population. Our goal is to understand the evolutionary role of social systems and its possible application as a non-genetic new step in evolutionary algorithms. In biological...
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| Format: | Conference or Workshop Item |
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2009
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| Online Access: | https://eprints.nottingham.ac.uk/34133/ |
| _version_ | 1848794780872474624 |
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| author | Lahoz-Beltra, Rafael Ochoa, Gabriela Aickelin, Uwe |
| author_facet | Lahoz-Beltra, Rafael Ochoa, Gabriela Aickelin, Uwe |
| author_sort | Lahoz-Beltra, Rafael |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | We propose a variation of the standard genetic algorithm that incorporates social interaction between the individuals in the population. Our goal is to understand the evolutionary role of social systems and its possible application as a non-genetic new step in evolutionary algorithms. In biological populations, i.e. animals, even human beings and microorganisms, social interactions often affect the fitness of individuals. It is conceivable that the perturbation of the fitness via social interactions is an evolutionary strategy to avoid trapping into local optimum, thus avoiding a fast convergence of the population. We model the social interactions according to Game Theory. The population is, therefore, composed by cooperator and defector individuals whose interactions produce payoffs according to well known game models (prisoner's dilemma, chicken game, and others). Our results on Knapsack problems show, for some game models, a significant performance improvement as compared to a standard genetic algorithm. |
| first_indexed | 2025-11-14T19:21:38Z |
| format | Conference or Workshop Item |
| id | nottingham-34133 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:21:38Z |
| publishDate | 2009 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-341332020-05-04T16:28:06Z https://eprints.nottingham.ac.uk/34133/ Cheating for problem solving: a genetic algorithm with social interactions Lahoz-Beltra, Rafael Ochoa, Gabriela Aickelin, Uwe We propose a variation of the standard genetic algorithm that incorporates social interaction between the individuals in the population. Our goal is to understand the evolutionary role of social systems and its possible application as a non-genetic new step in evolutionary algorithms. In biological populations, i.e. animals, even human beings and microorganisms, social interactions often affect the fitness of individuals. It is conceivable that the perturbation of the fitness via social interactions is an evolutionary strategy to avoid trapping into local optimum, thus avoiding a fast convergence of the population. We model the social interactions according to Game Theory. The population is, therefore, composed by cooperator and defector individuals whose interactions produce payoffs according to well known game models (prisoner's dilemma, chicken game, and others). Our results on Knapsack problems show, for some game models, a significant performance improvement as compared to a standard genetic algorithm. 2009-01-01 Conference or Workshop Item PeerReviewed Lahoz-Beltra, Rafael, Ochoa, Gabriela and Aickelin, Uwe (2009) Cheating for problem solving: a genetic algorithm with social interactions. In: GECCO '09: Proceedings of the Genetic and Evolutionary Computation Conference, 8-12 July 2009, Montreal, Canada. Genetic algorithms social interaction game theory knapsack problem http://dl.acm.org/citation.cfm?id=1570013 |
| spellingShingle | Genetic algorithms social interaction game theory knapsack problem Lahoz-Beltra, Rafael Ochoa, Gabriela Aickelin, Uwe Cheating for problem solving: a genetic algorithm with social interactions |
| title | Cheating for problem solving: a genetic algorithm with social interactions |
| title_full | Cheating for problem solving: a genetic algorithm with social interactions |
| title_fullStr | Cheating for problem solving: a genetic algorithm with social interactions |
| title_full_unstemmed | Cheating for problem solving: a genetic algorithm with social interactions |
| title_short | Cheating for problem solving: a genetic algorithm with social interactions |
| title_sort | cheating for problem solving: a genetic algorithm with social interactions |
| topic | Genetic algorithms social interaction game theory knapsack problem |
| url | https://eprints.nottingham.ac.uk/34133/ https://eprints.nottingham.ac.uk/34133/ |