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Machine translation of natural languages is one of the most complex and comprehensive applications of computational linguistics and artificial intelligence. This is especially true of knowledge-based machine translation (KBMT) systems, which require many knowledge resources and processing modules to carry out the necessary levels of analysis, representation and generation of meaning and form. The number of real-world problems, tasks, and solutions involved in developing any realistic-size knowledge-based machine translation system is enormous. It is thus difficult for researchers in the field to learn what a system "really does". This book fills that need with a detailed case study of a KBMT...
This unique volume focuses on computing systems that exhibit intelligent behavior. As such, it discusses research aimed at building a computer that has the same cognitive architecture as the mind -- permitting evaluations of it as a model of the mind -- and allowing for comparisons between computer performance and experimental data on human performance. It also examines architectures that permit large, complex computations to be performed -- and questions whether the computer so structured can handle these difficult tasks intelligently.
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Computer Systems and Software Engineering is a compilation of sixteen state-of-the-art lectures and keynote speeches given at the COMPEURO '92 conference. The contributions are from leading researchers, each of whom gives a new insight into subjects ranging from hardware design through parallelism to computer applications. The pragmatic flavour of the contributions makes the book a valuable asset for both researchers and designers alike. The book covers the following subjects: Hardware Design: memory technology, logic design, algorithms and architecture; Parallel Processing: programming, cellular neural networks and load balancing; Software Engineering: machine learning, logic programming and program correctness; Visualization: the graphical computer interface.
Case-based reasoning means reasoning based on remembering previous experiences. A reasoner using old experiences (cases) might use those cases to suggest solutions to problems, to point out potential problems with a solution being computed, to interpret a new situation and make predictions about what might happen, or to create arguments justifying some conclusion. A case-based reasoner solves new problems by remembering old situations and adapting their solutions. It interprets new situations by remembering old similar situations and comparing and contrasting the new one to old ones to see where it fits best. Case-based reasoning combines reasoning with learning. It spans the whole reasoning...
Analogy—recalling familiar past situations to deal with novel ones—is a mental tool that everyone uses. Analogy can provide invaluable creative insights, but it can also lead to dangerous errors. In Mental Leaps two leading cognitive scientists show how analogy works and how it can be used most effectively. Keith Holyoak and Paul Thagard provide a unified, comprehensive account of the diverse operations and applications of analogy, including problem solving, decision making, explanation, and communication. Holyoak and Thagard present their own theory of analogy, considering its implications for cognitive science in general, and survey examples from many other domains. These include anima...
Proceedings of the NATO Advanced Research Workshop on Data, Expert Knowledge and Decisions, held in Hamburg, FRG, September 3-5, 1989
This volume consists of a series of essays written by experts, most of whom participated in a conference conducted by the Educational Testing Service to explore how current fields of artificial intelligence might contribute to ETS's plans to automate one or more of its testing activities. The papers presented in Artificial Intelligence and the Future of Testing touch on a variety of topics including mathematics tutors, graph comprehension and computer vision, student reasoning and human accessing, modeling software design within a general problem-space architecture, memory organization and retrieval, and natural language systems. Also included: speculation on possible uses each AI specialty might have for a wide number of testing activities, and selective critical commentaries by two eminent AI researchers. As Roy Freedle notes in his introduction, "We are at an exciting juncture in applying AI to testing activities." The essays presented in this collection convey some of that excitement, and represent an important step toward the merging of AI and testing -- a powerful combination that has the potential to instruct and inspire.
Much of the cognitive lies beyond articulate, discursive thought, beyond the reach of current computational notions. In Sketches of Thought, Vinod Goel argues that the cognitive computational conception of the world requires our thought processes to be precise, rigid, discrete, and unambiguous; yet there are dense, ambiguous, and amorphous symbol systems, like sketching, painting, and poetry, found in the arts and much of everyday discourse that have an important, non-trivial place in cognition. Goel maintains that while on occasion our thoughts do conform to the current computational theory of mind, they often are - indeed must be - vague, fluid, ambiguous, and amorphous. He argues that if ...
The chapters in this collection illustrate how current concepts and principles from various disciplines can be viewed from the perspective of their value to educational process thinking. While not providing specific prescriptions for educational problems, the articles provide relevant experimental and theoretical knowledge has accumulated in many fields including learning theory, cognitive development, motivation, and intellectual abilities and attitudes.