The goal of this paper is to explore the effects of synchronization on distributed decision making processes. In particular, we examine the dynamics of a spatially distributed mul...
We apply an adapted version of Particle Swarm Optimization to distributed unsupervised robotic learning in groups of robots with only local information. The performance of the lea...
Inhabiting the complex and dynamic environments of modern computer games with autonomous agents capable of intelligent timely behaviour is a significant research challenge. We illu...
PAC-MDP algorithms approach the exploration-exploitation problem of reinforcement learning agents in an effective way which guarantees that with high probability, the algorithm pe...
In many settings, agents need to identify competent partners to assist them in accomplishing tasks. Direct experience may not provide sufficient data to learn the competence of ot...