Agent-oriented programming languages have gone a long way in the level of sophistication offered to programmers, and there has also been much progress in tools to support multi-ag...
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...
Since its inception, arti cial intelligence has relied upon a theoretical foundation centred around perfect rationality as the desired property of intelligent systems. We argue, a...
Stuart J. Russell, Devika Subramanian, Ronald Parr
We introduce a new method to find semantic inconsistencies (i.e., concepts with erroneous synonymity) in the Unified Medical Language System (UMLS). The idea is to identify the in...
One of the most difficult problems in Multi-Agent Systems (MAS) involves representing the knowledge and beliefs of an agent which performs its tasks in a dynamic environment. New p...