The problem of modeling a variety of domains within the framework of one general scheme is of central importance in AI. This paper presents the MultiEntity model for multi-agent p...
Multiagent learning di ers from standard machine learning in that most existing learning methods assume that all knowledge is available locally in a single agent. In multiagent sy...
Large scale multi-agent systems (MASs) in unpredictable environments must use machine learning techniques to perform their goals and improve the performance of the system. This pap...
We describe a system that successfully transfers value function knowledge across multiple subdomains of realtime strategy games in the context of multiagent reinforcement learning....
This paper describes the design, implementation, visualizations, results and lessons learned of a novel real-world socio-technical research system for the purpose of rescheduling ...
Erwin J. W. Abbink, David G. A. Mobach, Pieter-Jan...