Several multiagent reinforcement learning (MARL) algorithms have been proposed to optimize agents' decisions. Only a subset of these MARL algorithms both do not require agent...
Abstract. In multi-agent reinforcement learning systems, it is important to share a reward among all agents. We focus on the Rationality Theorem of Profit Sharing [5] and analyze ...
Interaction protocols are specific, often standard, constraints on the behaviors of autonomous agents in a multiagent system. Protocols are essential to the functioning of open sys...
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...
In recent years, mobile ad-hoc networks (MANET’s) have been deployed in various scenarios, but their scalability is severely restricted by the human operators’ ability to conf...