Bogdan Stanescu

Learn More
This paper presents the results of a multi-faceted research and development effort that synergistically integrates artificial intelligence research with military strategy research and practical deployment of agents into education. It describes recent advances in the Disciple approach to agent development by subject matter experts with limited assistance(More)
Over the years we have developed the Disciple theory, methodology, and family of tools for building knowledge-based agents. This approach consists of developing an agent shell that can be taught directly by a subject matter expert in a way that resembles how the expert would teach a human apprentice when solving problems in cooperation. This paper presents(More)
This paper presents new significant advances in the Disciple approach for building knowledge-based systems by subject matter experts. It describes the innovative application of this approach to the development of an agent for the analysis of strategic centers of gravity in military conflicts. This application has been deployed in several courses at the US(More)
This paper presents current results in developing a practical approach, methodology and tool, for the development of knowledge bases and agents by subject matter experts, with limited assistance from knowledge engineers. This approach is based on mixed-initiative reasoning that integrates the complementary knowledge and reasoning styles of a subject matter(More)
This paper presents an experiment of parallel knowledge base development by subject matter experts, performed as part of the DARPA's Rapid Knowledge Formation Program. It introduces the Disciple-RKF development environment used in this experiment and proposes design guidelines for systems that support authoring of problem solving knowledge by subject matter(More)
Ontologies and information sharing have a major role to play in the development of knowledge-based agents and the overcome of the knowledge acquisition bottleneck. This paper supports this claim by presenting an approach to ontology specification, import, and development that is part of Disciple-RKF. Disciple-RKF is a theory, methodology, and learning agent(More)
This paper presents a personal cognitive assistant, called Disciple-LTA, that can acquire expertise in intelligence analysis directly from intelligence analysts, can train new analysts, and can help analysts find solutions to complex problems through mixed-initiative reasoning, making possible the synergistic integration of a human's experience and(More)
This paper presents Disciple-RKF, a learning agent shell that can be used by subject matter experts, with limited assistance from knowledge engineers, to develop knowledge-based agents incorporating their expertise. 1. DISCIPLE-RKF LEARNING AGENT SHELL Disciple-RKF is a learning agent shell that represents the most recent implementation of Disciple, an(More)