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...
Abstract. This work merges ideas from two very different areas: Particle Swarm Optimisation and Evolutionary Game Theory. In particular, we are looking to integrate strategies from...
Moral emotions have been argued to play a central role in the emergence of cooperation in human-human interactions. This work describes an experiment which tests whether this insig...
This work presents a lookahead-based exploration strategy for a model-based learning agent that enables exploration of the opponent's behavior during interaction in a multi-a...
Agents that operate in a multi-agent system can benefit significantly from adapting to other agents while interacting with them. This work presents a general architecture for a ...