Game quantification is an expressive concept and has been studied in model theory and descriptive set theory, especially in relation to infinitary logics. Automatic structures on t...
Multiagent learning literature has investigated iterated twoplayer games to develop mechanisms that allow agents to learn to converge on Nash Equilibrium strategy profiles. Such ...
Reinforcement learning addresses the problem of learning to select actions in order to maximize one's performance inunknownenvironments. Toscale reinforcement learning to com...
A spoken language generation system has been developed that learns to describe objects in computer-generated visual scenes. The system is trained by a `show-and-tell' procedu...
We present Tartanian, a game theory-based player for headsup no-limit Texas Hold'em poker. Tartanian is built from three components. First, to deal with the virtually infinit...
Andrew Gilpin, Tuomas Sandholm, Troels Bjerre S&os...