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Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Adaptive global optimization with local search
Adaptive global optimization with local search
Adaptive individuals in evolving populations: models and algorithms
Adaptive individuals in evolving populations: models and algorithms
On evolutionary exploration and exploitation
Fundamenta Informaticae
Evolution and Optimum Seeking: The Sixth Generation
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Evolutionary Optimization in Dynamic Environments
Evolutionary Optimization in Dynamic Environments
Balancing Learning And Evolution
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Measurement of Population Diversity
Selected Papers from the 5th European Conference on Artificial Evolution
Increasing Population Diversity Through Cultural Learning
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Genetic algorithms with memory-and elitism-based immigrants in dynamic environments
Evolutionary Computation
The influence of learning on evolution: A mathematical framework
Artificial Life
A probabilistic memetic framework
IEEE Transactions on Evolutionary Computation
On the adaptive disadvantage of Lamarckianism in rapidly changing environments
ECAL'07 Proceedings of the 9th European conference on Advances in artificial life
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ECAL'05 Proceedings of the 8th European conference on Advances in Artificial Life
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IEEE Transactions on Evolutionary Computation
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IEEE Transactions on Evolutionary Computation
A tutorial for competent memetic algorithms: model, taxonomy, and design issues
IEEE Transactions on Evolutionary Computation
Classification of adaptive memetic algorithms: a comparative study
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A probabilistic memetic framework
IEEE Transactions on Evolutionary Computation
Exploration and exploitation in evolutionary algorithms: A survey
ACM Computing Surveys (CSUR)
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This article examines the interdependency of population-level adaptation (evolution) and individual-level adaptation (learning). More specifically, we assume a trade-off between the two means of adaptation, that is, a higher individual-level adaptation can only be achieved with a reduced population level adaptation and vice versa. This trade-off is apparent in computational evolutionary systems, and there is also evidence that it exists in nature. As we show, despite this considered trade-off, there exist environments in which a combined adaptation scheme is optimal. Furthermore, we demonstrate that the optimal adaptive behavior produced by a particular distribution of population- and individual-level adaptation depends on the environmental dynamics. Finally, we verify that the optimal balance (i.e., an optimal learning effort) can emerge from evolution when there is a trade-off between reproduction and lifetime.