Codynamic Fitness Landscapes of Coevolutionary Minimal Substrates
This work addresses the problem of understanding coevolutionary dynamics for researchers in evolutionary computation, but it appears incremental as it builds on existing models without major breakthroughs.
The paper tackled the challenge of analyzing fitness landscapes in coevolutionary problems by introducing similarity measures for codynamic fitness landscapes, and experimentally studied minimal substrates for test-based and compositional problems with cooperative and competitive interactions, though no concrete numerical results were reported.
Coevolutionary minimal substrates are simple and abstract models that allow studying the relationships and codynamics between objective and subjective fitness. Using these models an approach is presented for defining and analyzing fitness landscapes of coevolutionary problems. We devise similarity measures of codynamic fitness landscapes and experimentally study minimal substrates of test--based and compositional problems for both cooperative and competitive interaction.