We describe a generalized Q-learning type algorithm for reinforcement learning in competitive multi-agent games. We make the observation that in a competitive setting with adaptive...
Pieter Jan't Hoen, Sander M. Bohte, Han La Poutr&e...
We address the problem of transferring information learned from experiments to a different environment, in which only passive observations can be collected. We introduce a formal ...
Most of the existing 3D engines are overwhelmingly complex and do not integrate support for virtual characters. We have developed a teaching oriented 3D engine with support for su...
This paper is about people. It is about understanding how learning and communication mutually influence one another; allowing people to infer each other's communicative behavi...
This paper describes an algorithm, called CQ-learning, which learns to adapt the state representation for multi-agent systems in order to coordinate with other agents. We propose ...