8 research outputs found

    Machine learning research 1989-90

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    Multifunctional knowledge bases offer a significant advance in artificial intelligence because they can support numerous expert tasks within a domain. As a result they amortize the costs of building a knowledge base over multiple expert systems and they reduce the brittleness of each system. Due to the inevitable size and complexity of multifunctional knowledge bases, their construction and maintenance require knowledge engineering and acquisition tools that can automatically identify interactions between new and existing knowledge. Furthermore, their use requires software for accessing those portions of the knowledge base that coherently answer questions. Considerable progress was made in developing software for building and accessing multifunctional knowledge bases. A language was developed for representing knowledge, along with software tools for editing and displaying knowledge, a machine learning program for integrating new information into existing knowledge, and a question answering system for accessing the knowledge base

    Improving the explanation capabilities of advisory systems

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    A major limitation of current advisory systems (e.g., intelligent tutoring systems and expert systems) is their restricted ability to give explanations. The goal of our research is to develop and evaluate a flexible explanation facility, one that can dynamically generate responses to questions not anticipated by the system's designers and that can tailor these responses to individual users. To achieve this flexibility, we are developing a large knowledge base, a viewpoint construction facility, and a modeling facility. In the long term we plan to build and evaluate advisory systems with flexible explanation facilities for scientists in numerous domains. In the short term, we are focusing on a single complex domain in biological science, and we are working toward two important milestones: (1) building and evaluating an advisory system with a flexible explanation facility for freshman-level students studying biology, and (2) developing general methods and tools for building similar explanation facilities in other domains

    Generating referring expressions in a domain of objects and processes

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    This thesis presents a collection of algorithms and data structures for the generation of pronouns, anaphoric definite noun phrases, and one-anaphoric phrases. After a close analysis of the particular kinds of referring expressions that appear in a particular domain -that of cookery recipes -the thesis presents an appropriate ontology and a corresponding representation language. This ontology is then integrated into a wider framework for language generation as a whole, whereupon we show how the representation language can be successfully used to produce appropriate referring expressions for a range of complex object types.Amongst the more important ideas explored in the thesis are the following:• We introduce the notion of a generalized physical object as a way of representing singular entities, mass entities, and entities which are sets.• We adopt the view that planning operators are essentially underspecified events, and use this, in conjunction with a simple model of the hearer, to allow us to determine the appropriate level of detail at which a given plan should be described.• We make use of a discourse model that distinguishes local and global focus, and is closely tied to a notion of discourse structure; and we introduce a notion of DISCRIMINATORY POWER as a means to choosing the content of a referring expression.• We present a model of the generation of referring expressions that makes use of two levels of intermediate representation, and integrate this model with the use of a linguistically- founded grammar for noun phrases.The thesis ends by making some suggestions for further extensions to the work reported here

    Proceedings of the 1993 Conference on Intelligent Computer-Aided Training and Virtual Environment Technology

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    The volume 2 proceedings from the 1993 Conference on Intelligent Computer-Aided Training and Virtual Environment Technology are presented. Topics discussed include intelligent computer assisted training (ICAT) systems architectures, ICAT educational and medical applications, virtual environment (VE) training and assessment, human factors engineering and VE, ICAT theory and natural language processing, ICAT military applications, VE engineering applications, ICAT knowledge acquisition processes and applications, and ICAT aerospace applications

    Seventh Annual Workshop on Space Operations Applications and Research (SOAR 1993), volume 1

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    This document contains papers presented at the Space Operations, Applications and Research Symposium (SOAR) Symposium hosted by NASA/Johnson Space Center (JSC) on August 3-5, 1993, and held at JSC Gilruth Recreation Center. SOAR included NASA and USAF programmatic overview, plenary session, panel discussions, panel sessions, and exhibits. It invited technical papers in support of U.S. Army, U.S. Navy, Department of Energy, NASA, and USAF programs in the following areas: robotics and telepresence, automation and intelligent systems, human factors, life support, and space maintenance and servicing. SOAR was concerned with Government-sponsored research and development relevant to aerospace operations. More than 100 technical papers, 17 exhibits, a plenary session, several panel discussions, and several keynote speeches were included in SOAR '93

    The role of perspective in responding to property misconceptions

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    THE ROLE OF PERSPECTIVE IN RESPONDING TO PROPERTY MISCONCEPTIONS'

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    In order to adequately respond to misconceptions involving an object's properties, we must have a context-sensitive method for determining object similarity. Such a method is introduced here. Some of the necessary contextual information is captured by a new notion of object perspective. It is shown how object perspective can be used to account for different responses to a given misconception in different contexts. 1
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