The application of autonomous agents by the provisioning and usage of computational resources is an attractive research field. Various methods and technologies in the area of arti...
Nikolay Borissov, Arun Anandasivam, Niklas Wirstr&...
This paper presents a multi-agent reinforcement learning bidding approach (MARLBS) for performing multi-agent reinforcement learning. MARLBS integrates reinforcement learning, bid...
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 ...
Current turn-taking approaches for spoken dialogue systems rely on the speaker releasing the turn before the other can take it. This reliance results in restricted interactions th...
This paper investigates the problem of policy learning in multiagent environments using the stochastic game framework, which we briefly overview. We introduce two properties as de...