An adaptive agent model for self-organizing MAS

Self-organizing multi-agent systems (MAS) use different mechanisms to mimic the adaptation exhibited by complex systems situated in unpredictable and dynamic environments. These mechanisms allow a collection of agents to spontaneously adapt their behavior towards an optimal organization. This paper presents a self-organization approach that exploits several self-organizing principles through an agent adaptive architecture and a reinforcement mechanism. This mechanism was designed and implemented using the INGENIAS methodology.