Abstract— This paper compares the use of temporal difference learning (TDL) versus co-evolutionary learning (CEL) for acquiring position evaluation functions for the game of Othe...
We introduce relational temporal difference learning as an effective approach to solving multi-agent Markov decision problems with large state spaces. Our algorithm uses temporal ...
Video game players often learn to map their physical actions (e.g., pressing buttons) onto their on-screen avatars' actions (e.g., wielding swords) in order to play. We explo...
This work explores the intersection between infographics and games by examining how to embed meaningful visual analytic interactions into game mechanics that in turn impact user b...
Nicholas Diakopoulos, Funda Kivran-Swaine, Mor Naa...
Abstract In this paper we address the problem of simultaneous learning and coordination in multiagent Markov decision problems (MMDPs) with infinite state-spaces. We separate this ...