Cristian Levcovici

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This paper presents Disciple-COA, the most recent learning agent shell developed in the Disciple framework that aims at changing the way an intelligent agent is built: from “being programmed” by a knowledge engineer, to “being taught” by a domain expert. Disciple-COA can collaborate with the expert to develop its knowledge base consisting of a frame-based(More)
This paper presents a practical learning-based methodology and agent shell for building knowledge bases and knowledge-based agents, and their innovative application to the development of a critiquing agent for military courses of action, a challenge problem set by DARPA’s High Performance Knowledge Bases program. The agent shell consists of an integrated(More)
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