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This paper proposes a multiagent approach for metaheuristics hybridization inspired on the popular technique called Particle Swarm Optimization (PSO). In the proposed approach, agents develop a society with collaboration to achieve their own individual as well as common goals and their decision-making process matches the basic nature of a particle in the PSO framework. Each particle is an autonomous agent with memory and methods for learning and making decisions. The proposed approach isdoi:10.1109/sbrn.2012.39 dblp:conf/sbrn/SouzaGGC12 fatcat:szpkdgkeq5axng2izz6setuzwm