Browsing by Author "Moura, Paulo Oliveira"
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- Case-based reasoning for meta-heuristics self-parameterization in a multi-agent scheduling systemPublication . Pereira, Ivo; Madureira, Ana Maria; Moura, Paulo OliveiraA 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.
- Meta-heuristics self-parameterization in a multi-agent scheduling system using case-based reasoningPublication . Pereira, Ivo; Madureira, Ana Maria; Moura, Paulo OliveiraThis paper proposes a novel agent-based approach to Meta-Heuristics self-configuration. Meta-heuristics are algorithms with parameters which need to be set up as efficient as possible in order to unsure its performance. A learning module for self-parameterization of Meta-heuristics (MH) in a Multi-Agent System (MAS) for resolution of scheduling problems is proposed in this work. The learning module 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. Finally, some conclusions are reached and future work outlined.
- Multi-apprentice learning for meta-heuristics parameter tuning in a multi agent scheduling systemPublication . Pereira, Ivo; Madureira, Ana Maria; Moura, Paulo OliveiraThe scheduling problem is considered in complexity theory as a NP-hard combinatorial optimization problem. Meta-heuristics proved to be very useful in the resolution of this class of problems. However, these techniques require parameter tuning which is a very hard task to perform. A Case-based Reasoning module is proposed in order to solve the parameter tuning problem in a Multi-Agent Scheduling System. A computational study is performed in order to evaluate the proposed CBR module performance.