MadKit: a generic multi-agent platform
AGENTS '00 Proceedings of the fourth international conference on Autonomous agents
An improved GA and a novel PSO-GA-based hybrid algorithm
Information Processing Letters
A new distributed particle swarm optimization algorithm for constraint reasoning
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part II
Enhancements of branch and bound methods for the maximal constraint satisfaction problem
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Load Balancing for the Dynamic Distributed Double Guided Genetic Algorithm for MAX-CSPs
International Journal of Artificial Life Research
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In this paper the authors propose a new distributed double guided hybrid algorithm combining the particle swarm optimization PSO with genetic algorithms GA to resolve maximal constraint satisfaction problems Max-CSPs. It consists on a multi-agent approach inspired by a centralized version of hybrid algorithm called Genetical Swarm Optimization GSO. Their approach consists of a set of evolutionary agents dynamically created and cooperating in order to find an optimal solution. Each agent executes its own hybrid algorithm and it is able to compute its own parameters. The authors' approach is compared to the GSO. It demonstrates its superiority. They reached these results thanks to the distribution using multi-agent systems, diversification and intensification mechanisms.