Partnering Strategies for Fitness Evaluation in a Pyramidal Evolutionary Algorithm
University of the West of England（西英格兰大学）
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
