In recent years there has been a great deal of interest in "modular reinforcement learning" (MRL). Typically, problems are decomposed into concurrent subgoals, allowing ...
Sooraj Bhat, Charles Lee Isbell Jr., Michael Matea...
Many problem-solving tasks can be formalized as constraint satisfaction problems (CSPs). In a multi-agent setting, information about constraints and variables may belong to differ...
Because of privacy concerns, agents may not want to reveal information that could be of use in problem solving. As a result, there are potentially important tradeoffs between main...
This paper studies bilateral multi-issue negotiation between self-interested agents. The outcome of such encounters depends on two key factors: the agenda (i.e., the set of issues...
S. Shaheen Fatima, Michael Wooldridge, Nicholas R....
Schulenburg [15] first proposed the idea to model different trader types by supplying different input information sets to a group of homogenous LCS agent. Gershoff [12] investigat...