How learning can guide evolution
Adaptive individuals in evolving populations
How Symbiosis Can Guide Evolution
ECAL '99 Proceedings of the 5th European Conference on Advances in Artificial Life
When Both Individuals and Populations Search: Adding Simple Learning to the Genetic Algorithm
Proceedings of the 3rd International Conference on Genetic Algorithms
The Puzzle of the Persistent Question Marks: A Case Study of Genetic Drift
Proceedings of the 5th International Conference on Genetic Algorithms
Animats in the Modeling Ecosystem
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
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The Baldwin Effect indicates that individually learned behaviours acquired during an organism’s lifetime can influence the evolutionary path taken by a population, without any direct Lamarckian transfer of traits from phenotype to genotype. Several computational studies modelling this effect have included complications that restrict its applicability. Here we present a simplified model that is used to reveal the essential mechanisms and highlight several conceptual issues that have not been clearly defined in prior literature. In particular, we suggest that canalisation and genetic assimilation, often conflated in previous studies, are separate concepts and the former is actually not required for non-heritable phenotypic variation to guide genetic variation. Additionally, learning, often considered to be essential for the Baldwin Effect, can be replaced with a more general phenotypic plasticity model. These simplifications potentially permit the Baldwin Effect to operate in much more general circumstances.