We propose and study a technique to improve the performance of those local-search SAT solvers that proceed by executing a prespecified number of tries, each starting with an eleme...
Learning in many multi-agent settings is inherently repeated play. This calls into question the naive application of single play Nash equilibria in multi-agent learning and sugges...
A game-theoretic approach for learning optimal parameter values for probabilistic rough set regions is presented. The parameters can be used to define approximation regions in a p...
—This paper considers distributed protocol design for joint sub-carrier, transmission scheduling and power management in uplink/downlink multi-cellular OFDMA wireless networks. T...
Cooperative negotiation is proved to be an effective paradigm to solve complex dynamic multi-objective problems in which each objective is associated to an agent. When the multi-o...