Abstract
Within the framework of constraint reasoning we introduce a newer distributed particle swarm approach. The latter is a new multi-agent approach which addresses additive Constraint Satisfaction problems ((CSPs). It is inspired by the dynamic distributed double guided genetic algorithm (D3G2A) for Constraint reasoning. It consists of agents dynamically created and cooperating in order to solve problems. Each agent performs locally its own particle swarm optimization algorithm (PSO). This algorithm is slightly different from other PSO algorithms. As well, not only do the new approach parameters allow diversification but also permit escaping from local optima. Second,. Experimentations are held to show effectiveness of our approach.
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Bouamama, S. (2010). A New Distributed Particle Swarm Optimization Algorithm for Constraint Reasoning. In: Setchi, R., Jordanov, I., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based and Intelligent Information and Engineering Systems. KES 2010. Lecture Notes in Computer Science(), vol 6277. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15390-7_32
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DOI: https://doi.org/10.1007/978-3-642-15390-7_32
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