@inproceedings { , title = {Partnering Strategies for Fitness Evaluation in a Pyramidal Evolutionary Algorithm}, abstract = {This paper combines the idea of a hierarchical distributed genetic algorithm with different inter-agent partnering strategies. Cascading clusters of sub-populations are built from bottom up, with higher-level sub-populations optimising larger parts of the problem. Hence higher-level sub-populations search a larger search space with a lower resolution whilst lower-level sub-populations search a smaller search space with a higher resolution. The effects of different partner selection schemes for (sub-)fitness evaluation purposes are examined for two multiple-choice optimisation problems. It is shown that random partnering strategies perform best by providing better sampling and more diversity.}, conference = {Genetic and Evolutionary Computation Conference}, organization = {New York, USA}, publicationstatus = {Published}, url = {https://nottingham-repository.worktribe.com/output/1022640}, year = {2002}, author = {Aickelin, Uwe and Bull, Larry} }