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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)
— This paper presents an approach to rapid development of virtual planning experts that can collaborate to develop plans of action requiring expertise from multiple domains. The approach is implemented into a new type of software tool, called Disciple-VPT, which includes an exten-sible library of virtual planning experts from different domains. Teams of(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 introduces the concept of learning agent shell as a new class of tools for rapid development of practical end-to-end knowledge-based agents, by domain experts, with limited assistance from knowledge engineers. A learning agent shell consists of a learning and knowledge acquisition engine as well as an inference engine and supports building an(More)
methodology for building knowledge bases and agents and their innovative application to the development of a critiquing agent for military courses of action, a challenge problem set by the Defense Advanced Research Projects Agency's High-Performance Knowledge Bases Program. The learning agent shell includes a general problem-solving engine and a general(More)
— This paper presents elements of a computational theory of intelligence analysis and its implementation in a cognitive assistant. Following the framework of the scientific method, this theory provides computational models for essential analysis tasks: evidence marshaling for hypotheses generation, hypotheses-driven evidence collection, and hypotheses(More)
Editorial Introduction agents, assuming they work independently , or they can achieve the same goals more effectively. Mixed initiative assumes an efficient, natural in-terleaving of contributions by users and automated agents that is determined by their relative knowledge and skills and the problem-solving context , rather than by fixed roles, enabling(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)
This paper presents a successful knowledge acquisition experiment in which subject matter experts that did not have any prior knowledge engineering experience succeeded to teach the Disciple-COA agent how to critique courses of action, a challenge problem addressed by the DARPA's High Performance Knowledge Bases program. We first present the COA challenge(More)