2026-07-072026-07-07http://salesiana.dossiersoluciones.com/handle/123456789/32747Research concerning organization and coordination within multi-agent systems continues to draw from a variety of architectures and methodologies. The work presented in this paper combines techniques from game theory and multi-agent systems to produce self-organizing, polymorphic, lightweight, embedded agents for systems scheduling within a large-scale real-time systems environment. Results show how this approach is used to experimentally produce optimum real-time scheduling through the emergent behavior of thousands of agents. These results are obtained using a SWARM simulation of systems scheduling within a High Energy Physics experiment consisting of 2500 digital signal processors.Fourth International Conference on Hybrid Intelligent Systems (HIS), Kitakyushu, Japan, December, 2004Artificial IntelligenceMultiagent Systemstext