Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
Evidence for self-organized criticality in evolution
Proceedings of the 16th annual international conference of the Center for Nonlinear Studies on Landscape paradigms in physics and biology : concepts, structures and dynamics: concepts, structures and dynamics
Simulation Modeling and Analysis
Simulation Modeling and Analysis
On Evolving Robust Strategies for Iterated Prisoner's Dilemma
AI '93/AI '94 Selected papers from the AI'93 and AI'94 Workshops on Evolutionary Computation, Process in Evolutionary Computation
Crossover, Macromutationand, and Population-Based Search
Proceedings of the 6th International Conference on Genetic Algorithms
Building Blocks, Cohort Genetic Algorithms, and Hyperplane-Defined Functions
Evolutionary Computation
Behavioral diversity, choices and noise in the iterated prisoner's dilemma
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Evolutionary Computation
A strategy with novel evolutionary features for the iterated prisoner's dilemma
Evolutionary Computation
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We examine the role played by crossover in a series of genetic algorithm-based evolutionary simulations of the iterated prisoner's dilemma. The simulations are characterized by extended periods of stability, during which evolutionarily meta-stable strategies remain more or less fixed in the population, interrupted by transient, unstable episodes triggered by the appearance of adaptively targeted predators. This leads to a global evolutionary pattern whereby the population shifts from one of a few evolutionarily metastable strategies to another to evade emerging predator strategies. While crossover is not particularly helpful in producing better average scores, it markedly enhances overall evolutionary stability. We show that crossover achieves this by (1) impeding the appearance and spread of targeted predator strategies during stable phases, and (2) greatly reducing the duration of unstable epochs, presumably by efficient recombination of building blocks to rediscover prior metastable strategies. We also speculate that during stable phases, crossover's operation on the persistently heterogeneous gene pool enhances the survival of useful building blocks, thus sustaining long-range temporal correlations in the evolving population. Empirical support for this conjecture is found in the extended tails of probability distribution functions for stable phase lifetimes.