Case-based Reasoning for Meta-heuristics Self-Parameterization in a Multi-Agent Scheduling System
نویسندگان
چکیده
A novel agent-based approach to Meta-Heuristics self-configuration is proposed in this work. Meta-heuristics are examples of algorithms where parameters need to be set up as efficient as possible in order to unsure its performance. This paper presents a learning module for self-parameterization of Meta-heuristics (MHs) in a Multi-Agent System (MAS) for resolution of scheduling problems. The learning is based on Case-based Reasoning (CBR) and two different integration approaches are proposed. A computational study is made for comparing the two CBR integration perspectives. In the end, some conclusions are reached and future work outlined. KeywordsCase-based Reasoning, Learning, Metaheuristics, Multi-Agent Systems, Scheduling
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