—Multi-robot reinforcement learning is a very challenging area due to several issues, such as large state spaces, difficulty in reward assignment, nondeterministic action selecti...
This paper presents J-MADeM, a multi-modal decision making mechanism to provide agents in a Multi-Agent Systems (MAS) with a market-based model for complex decision problems. J-MA...
Francisco Grimaldo, Miguel Lozano, Fernando Barber
We propose a novel approach to intelligent tutoring gaming simulations designed for both educational and inquiry purposes in complex multi-actor systems such as infrastructures or...
This paper offers a novel approach to coevolution based on the sociological theory of symbolic interactionism. It provides a multi-agent computational model along with experimenta...
We develop an interference alignment (IA) technique for a downlink cellular system. In the uplink, IA schemes need channel-state-information exchange across base-stations of diffe...