One of the most challenging aspects of reasoning, planning, and acting in a multi-agent domain is reasoning about what the agents know about the knowledge of their fellows, and to...
Chitta Baral, Gregory Gelfond, Tran Cao Son, Enric...
Distributed Constraints Optimization (DCOP) is a powerful framework for representing and solving distributed combinatorial problems, where the variables of the problem are owned b...
Alon Grubshtein, Roie Zivan, Tal Grinshpoun, Amnon...
Virtual human research has often modeled nonverbal behaviors based on the findings of psychological research. In recent years, however, there have been growing efforts to use auto...
Developing a robust, flexible, closed-loop walking algorithm for a humanoid robot is a challenging task due to the complex dynamics of the general biped walk. Common analytical ap...
The goal of testing is to discriminate between multiple hypotheses about a system--for example, different fault diagnoses--by applying input patterns and verifying or falsifying t...
Many computational problems in game theory, such as finding Nash equilibria, are algorithmically hard to solve. This limitation forces analysts to limit attention to restricted su...
When merging belief sets from different agents, the result is normally a consistent belief set in which the inconsistency between the original sources is not represented. As proba...