Negotiation techniques have been demonstrated to be effective in solving complex multi-objective problems. When the optimization process operates on continuous variables, it can b...
Abstract— We describe a decentralized learning-based activation algorithm for a ZigBee-enabled unattended ground sensor network. Sensor nodes learn to monitor their environment i...
We consider a game-theoretical variant of the Steiner forest problem in which each player j, out of a set of k players, strives to connect his terminal pair (sj, tj) of vertices in...
Learning to converge to an efficient, i.e., Pareto-optimal Nash equilibrium of the repeated game is an open problem in multiagent learning. Our goal is to facilitate the learning ...
We demonstrate two game theory-based programs for headsup limit and no-limit Texas Hold'em poker. The first player, GS3, is designed for playing limit Texas Hold'em, in ...
Andrew Gilpin, Tuomas Sandholm, Troels Bjerre S&os...