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Mixed-initiative assistants are agents that interact seamlessly with humans to extend their problem solving capabilities or provide new capabilities. Developing such agents requires the synergistic integration of many areas of AI, including knowledge representation, problem solving and planning, knowledge acquisition and learning, multi-agent systems,(More)
This paper addresses the problem of improving the representation space in a rule-based intelligent system, through exception-based learning. Such a system generally learns rules containing exceptions because its representation language is incomplete. However, these exceptions suggest what may be missing from the system's ontology, which is the basis of the(More)
—This paper presents results on developing a general intelligence analysis ontology which is part of the knowledge base of Disciple-LTA, a unique and complex cognitive assistant for evidence-based hypothesis analysis that helps an intelligence analyst cope with many of the complexities of intelligence analysis. It introduces the cognitive assistant and(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)
This paper discusses several critical capabilities of the Disciple-LTA system for complex problem-solving and decision-making, including a transparent and easy to understand reasoning process, a flexible and natural collaboration with the user, and the use of what-if scenarios to cope with incomplete and uncertain information. They allow the user to act as(More)
This paper presents a learning-based representation of knowledge which is at the basis of the family of Disciple learning agents. It introduces a representation for concepts, generalization and specialization rules, different types of generalizations and specializations, and the representation of the main elements of a knowledge base, including partially(More)