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Computational Models of Discourse
304
Jarice Hanson
An interesting compendium of information with the perspective grounded in psychological models of understanding. Sections of particular interest to individuals interested in the psychological aspects of using artificial intelligence are those which deal with "The Case for a Cognitive Biology,.... Real World Reasoning," "Freudian Mechanisms of Defense: A Programming Perspective," "Artificial Intelligence and Piagetian Theory," and "Human Values in a Mechanistic Universe." This book offers a unique interpretation and is strongly suggested as a supplement to strict artificial intelligence theory and mechanistic models.
Brady, M. and Berwick, Robert (Eds). Computational Models of Discourse (Cambridge, MA.: MIT Press, 1983, 403pp). A collection of articles in all aspects of the computational aspects of discourse such as natural language intention, using query systems, and the comprehension available.
Buchanan, Bruce, and Shortliffe, Edward. Rule-Based Expert Systems: The MYCIN Experiments of the Stanford Heuristic Programming Project (Reading, MA.: AddisonWesley Publishing Co., 1984, 748pp). A specific approach and explanation, the authors give fair detail to the particulars of the experience.
Bundy, A. (Ed.) Artificial Intelligence: An Introductory Course (Edinburgh: University Press, 1978, 252pp). An early approach to the basics with chapters on Problem Solving; Natural Language; Question Answering and Inference; Visual Perception; Learning; and Programming, with Appendices.
Charniak, Eugene, Riesbeck, Christopher K. and McDermott, Drew V. Artificial Intelligence Programming (Hillsdale, N J: Lawrence Erlbaum Associates, 1980, 323pp). The twenty different chapters provide a wide variety of tools for programming artificial intelligence theories, such as discrimination nets, agendas, deduction, data dependencies, and others. The techniques described are more appropriate for the abstract end of AI rather than the concrete end.
Davis, Randall, and Lenat, Douglas B. Knowledge Based Systems in Artificial Intelligence (N.Y.: McGraw-Hill, 1982,490pp). The authors take the perspective that the knowledge-based paradigm is more appropriate than the inference-based paradigm. In two parts, they discuss "AM: Discovery in Mathematics as Heuristic Search," and "Teiresias: Applications of Meta-Level Knowledge."
Jarice Hanson
An interesting compendium of information with the perspective grounded in psychological models of understanding. Sections of particular interest to individuals interested in the psychological aspects of using artificial intelligence are those which deal with "The Case for a Cognitive Biology,.... Real World Reasoning," "Freudian Mechanisms of Defense: A Programming Perspective," "Artificial Intelligence and Piagetian Theory," and "Human Values in a Mechanistic Universe." This book offers a unique interpretation and is strongly suggested as a supplement to strict artificial intelligence theory and mechanistic models.
Brady, M. and Berwick, Robert (Eds). Computational Models of Discourse (Cambridge, MA.: MIT Press, 1983, 403pp). A collection of articles in all aspects of the computational aspects of discourse such as natural language intention, using query systems, and the comprehension available.
Buchanan, Bruce, and Shortliffe, Edward. Rule-Based Expert Systems: The MYCIN Experiments of the Stanford Heuristic Programming Project (Reading, MA.: AddisonWesley Publishing Co., 1984, 748pp). A specific approach and explanation, the authors give fair detail to the particulars of the experience.
Bundy, A. (Ed.) Artificial Intelligence: An Introductory Course (Edinburgh: University Press, 1978, 252pp). An early approach to the basics with chapters on Problem Solving; Natural Language; Question Answering and Inference; Visual Perception; Learning; and Programming, with Appendices.
Charniak, Eugene, Riesbeck, Christopher K. and McDermott, Drew V. Artificial Intelligence Programming (Hillsdale, N J: Lawrence Erlbaum Associates, 1980, 323pp). The twenty different chapters provide a wide variety of tools for programming artificial intelligence theories, such as discrimination nets, agendas, deduction, data dependencies, and others. The techniques described are more appropriate for the abstract end of AI rather than the concrete end.
Davis, Randall, and Lenat, Douglas B. Knowledge Based Systems in Artificial Intelligence (N.Y.: McGraw-Hill, 1982,490pp). The authors take the perspective that the knowledge-based paradigm is more appropriate than the inference-based paradigm. In two parts, they discuss "AM: Discovery in Mathematics as Heuristic Search," and "Teiresias: Applications of Meta-Level Knowledge."