In multiagent adversarial domains, team agents should adapt to the environment and opponent. We introduce a model representation as part of a planning process for a simulated socce...
We consider multi-agent systems whose agents compete for resources by striving to be in the minority group. The agents adapt to the environment by reinforcement learning of the pr...
Abstract. We study the exchange of information in collective information systems mediated by information agents, focusing specifically on the problem of semantic interoperability. ...
Most standard learning algorithms, such as Logistic Regression (LR) and the Support Vector Machine (SVM), are designed to deal with i.i.d. (independent and identically distributed...
Chi-Hoon Lee, Matthew R. G. Brown, Russell Greiner...
1 We have developed an approach to acquire complicated user optimization criteria and use them to guide iterative solution improvement. The eectiveness of the approach was tested ...