In this paper, we propose a logical approach to represent and reason about different time granularities. We identify a time granularity as a discrete infinite sequence of time po...
This paper presents CBRetaliate, an agent that combines Case-Based Reasoning (CBR) and Reinforcement Learning (RL) algorithms. Unlike most previous work where RL is used to improve...
Bryan Auslander, Stephen Lee-Urban, Chad Hogg, H&e...
Large scale ontology applications require efficient and robust description logic (DL) reasoning services. Expressive DLs usually have very high worst case complexity while tractab...
Reasoning about the past is of fundamental importance in several applications in computer science and artificial intelligence, including reactive systems and planning. In this pa...
In previous work, Levesque proposed an extension to classical databases that would allow for a certain form of incomplete first-order knowledge. Since this extension was suffici...