Evolutionary Optimization in Dynamic Environments
Evolutionary Optimization in Dynamic Environments
On the Utility of Redundant Encodings in Mutation-Based Evolutionary Search
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
Genotype-Phenotype-Mapping and Neutral Variation - A Case Study in Genetic Programming
PPSN III Proceedings of the International Conference on Evolutionary Computation. The Third Conference on Parallel Problem Solving from Nature: Parallel Problem Solving from Nature
Neutrality and the Evolvability of Boolean Function Landscape
EuroGP '01 Proceedings of the 4th European Conference on Genetic Programming
Redundant representations in evolutionary computation
Evolutionary Computation
Designing Evolutionary Algorithms for Dynamic Environments
Designing Evolutionary Algorithms for Dynamic Environments
Representations for Genetic and Evolutionary Algorithms
Representations for Genetic and Evolutionary Algorithms
Natural Computing: an international journal
Natural Computing: an international journal
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It has been proposed that degeneracy plays a fundamental role in biological evolution by facilitating robustness and adaptation within heterogeneous and time-variant environments. Degeneracy occurs whenever structurally distinct agents display similar functions within some contexts but unique functions in others. In order to test the broader applicability of this hypothesis, especially to the field of evolutionary dynamic optimisation, we evolve multi-agent systems (MAS) in time-variant environments and investigate how degeneracy amongst agents influences the system's robustness and evolvability. We find that degeneracy freely emerges within our framework, leading to MAS architectures that are robust towards a set of similar environments and quickly adaptable to large environmental changes. Detailed supplementary experiments, aimed particularly at the scaling behaviour of these results, demonstrate a broad range of validity for our findings and suggest that important general distinctions may exist between evolution in degenerate and non-degenerate agent-based systems.