In large systems, it is important for agents to learn to act effectively, but sophisticated multi-agent learning algorithms generally do not scale. An alternative approach is to ï...
In this paper, we describe a nature-inspired optimization algorithm based on bee foraging behavior. This algorithm combines the high performance of bee path-integration navigation...
Decentralized partially observable MDPs (DEC-POMDPs) provide a rich framework for modeling decision making by a team of agents. Despite rapid progress in this area, the limited sc...
Decentralized partially observable Markov decision processes (Dec-POMDPs) constitute a generic and expressive framework for multiagent planning under uncertainty. However, plannin...
Frans A. Oliehoek, Shimon Whiteson, Matthijs T. J....
Reasoning about others, as performed by agents in order to coordinate their behaviours with those of others, commonly involves forming and updating beliefs about hidden system pro...