We build the generic methodology based on machine learning and reasoning to detect the patterns of interaction between conflicting agents, including humans and their assistants. L...
Agents are systems capable of perceiving their environment through sensors, reasoning about their sensory input using some characteristic reasoning process and acting in their env...
Retrieving relevant information in Data and Knowledge Bases containing a large number of di erent types of information is a non trivial problem. That is the reason why, in areas l...
In an open Multi-Agent System, the goals of agents acting on behalf of their owners often conflict with each other. Therefore, a personal agent protecting the interest of a single...
Ruben Stranders, Mathijs de Weerdt, Cees Witteveen
In our research we study rational agents which learn how to choose the best conditional, partial plan in any situation. The agent uses an incomplete symbolic inference engine, emp...