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 use reinforcement learning (RL) to compute strategies for multiagent soccer teams. RL may pro t signi cantly from world models (WMs) estimating state transition probabilities an...
The existing reinforcement learning approaches have been suffering from the policy alternation of others in multiagent dynamic environments such as RoboCup competitions since othe...
In this paper we describe an integrated multilevel learning approach to multiagent coalition formation in a real-time environment. In our domain, agents negotiate to form teams to...
Petroleum industry production systems are highly automatized. In this industry, all functions (e.g., planning, scheduling and maintenance) are automated and in order to remain comp...