In this paper, we use computational intelligence techniques to built quantitative models of player experience for a platform game. The models accurately predict certain key affecti...
Christopher Pedersen, Julian Togelius, Georgios N....
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...
This paper describes the current state of our ongoing work developing tools for tracking player enjoyment in traditional face-to-face tabletop gaming situations. The challenge pre...
Abstract. We introduce model-checking games that allow local secondorder power on sets of independent transitions in the underlying partial order models where the games are played....