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Case-based reasoning for self-optimizing behavior
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Orientador(es)
Resumo(s)
In this paper we present a Self-Optimizing
module, inspired on Autonomic Computing, acquiring a
scheduling system with the ability to automatically select a
Meta-heuristic to use in the optimization process, so as its
parameterization. Case-based Reasoning was used so the
system may be able of learning from the acquired experience,
in the resolution of similar problems. From the obtained
results we conclude about the benefit of its use.
Descrição
Palavras-chave
Multi-agent learning Self-optimizing Casebased reasoning