Many multiagent problems comprise subtasks which can be considered as reinforcement learning (RL) problems. In addition to classical temporal difference methods, evolutionary algo...
Jan Hendrik Metzen, Mark Edgington, Yohannes Kassa...
There is growing interest in multi-robot frequency-based patrolling, in which a team of robots optimizes its frequency of point visits, for every point in a target work area. In p...
Multiagent coordination algorithms provide unique insights into the challenging problem of alleviating traffic congestion. What is particularly interesting in this class of proble...
Effective norms, emerging from sustained individual interactions over time, can complement societal rules and significantly enhance performance of individual agents and agent soci...
In many multiagent settings, each agent's goal is to come out ahead of the other agents on some metric, such as the currency obtained by the agent. In such settings, it is no...