Computability and logic
Adaptive individuals in evolving populations: models and algorithms
Adaptive individuals in evolving populations: models and algorithms
New ideas in optimization
Artificial Life
Reverse HillclimbingGenetic Algorithms and the Busy Beaver Problem
Proceedings of the 5th International Conference on Genetic Algorithms
SEAL'98 Selected papers from the Second Asia-Pacific Conference on Simulated Evolution and Learning on Simulated Evolution and Learning
Lamarckian Evolution, The Baldwin Effect and Function Optimization
PPSN III Proceedings of the International Conference on Evolutionary Computation. The Third Conference on Parallel Problem Solving from Nature: Parallel Problem Solving from Nature
Busy Beaver - The Influence of Representation
Proceedings of the Second European Workshop on Genetic Programming
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The goal of this research is to study how individual learning interacts with an evolutionary algorithm in its search for good candidates for the Busy Beaver problem. Two learning models, designed to act as local search procedures, are proposed. Experimental results show that local search methods that are able to perform several modifications in the structure of an individual in each learning step provide an important advantage. Some insight about the role that evolution and learning play during search is also presented.