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Adaptation using hybridized genetic crossover strategies
- Source :
- Physica A: Statistical Mechanics and its Applications. 322:701-709
- Publication Year :
- 2003
- Publisher :
- Elsevier BV, 2003.
-
Abstract
- We present a simple game which mimics the complex dynamics found in most natural and social systems. Intelligent players modify their strategies periodically, depending on their performances. We propose that the agents use hybridized one-point genetic crossover mechanism,inspired by genetic evolution in biology, to modify the strategies and replace the bad strategies. We study the performances of the agents under different conditions and investigate how they adapt themselves in order to survive or be the best, by finding new strategies using the highly effective mechanism we proposed.<br />4 pages, 4 eps figures. Uses REVTeX
- Subjects :
- Statistics and Probability
Statistical Mechanics (cond-mat.stat-mech)
Mechanism (biology)
business.industry
Crossover
FOS: Physical sciences
Condensed Matter Physics
Quantitative Biology
Complex dynamics
Genetic Evolution
FOS: Biological sciences
Artificial intelligence
Adaptation (computer science)
business
Quantitative Biology (q-bio)
Condensed Matter - Statistical Mechanics
Subjects
Details
- ISSN :
- 03784371
- Volume :
- 322
- Database :
- OpenAIRE
- Journal :
- Physica A: Statistical Mechanics and its Applications
- Accession number :
- edsair.doi.dedup.....bdda702809836bf0ff0453339a08aa32
- Full Text :
- https://doi.org/10.1016/s0378-4371(02)01827-7