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Foundations of Knowledge Acquisition : Cognitive Models of Complex Learning :  Cognitive Models of Complex Learning - Susan F. Chipman

Foundations of Knowledge Acquisition : Cognitive Models of Complex Learning

Cognitive Models of Complex Learning

By: Susan F. Chipman (Editor), Alan L. Meyrowitz (Editor)

Hardcover Published: December 2009
ISBN: 9780792392774
Number Of Pages: 339

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The two volumes of Foundations of Knowledge Acquisition document the recent progress of basic research in knowledge acquisition sponsored by the Office of Naval Research. This volume is subtitled Cognitive Models of Complex Learning, and there is a companion volume, subtitles Machine Learning. Funding was provided by a five-year Accelerated Research Initiative (ARI), and made possible significant advances in the scientific understanding of how machines and humans can acquire new knowledge so as to exhibit improved problem-solving behavior. Knowledge acquisition, as persued under the ARI, was a coordinated research thrust into both machine learning and the human learning. Chapters in Cognitive Models of Complex Learning thus include summaries of work by cognitive scientists who do computational modeling of human learning. In fact, an accomplishment of research previously sponsored by ONR's Cognitive Science Program gave insight into the knowledge and skills that distinguish human novices from human experts in various domains; the cognitive interest in the ARI was then to characterize how the transition form novice to expert actually takes place. Chapters particularly relevant to that concern are those written by Anderson, Kieras, Marshall, Ohlsson, and VanLehn. Significant progress in machine learning is reported along in a variety of fronts in the companion volume, Machine Learning, also published by Kluwer Academic Publishers. Included is work in analogical reasoning; induction and discovery; explanation-based learning; learning by competition, using genetic algorithms; learning within natural language systems; theoretical limitations, learning in Soar, a proposed general architecture for intelligent systems; and case-based reasoning. These volumes of Foundations of Knowledge Acquisition are excellent reference sources by bringing together descriptions of recent and ongoing research at the forefront of progress in one the most challenging arenas of artificial intelligence and cognitive science. In addition, contributing authors comment on ecxiting future directions for research.

Foreword. Preface. 1. Acquisition of LISP Programming Skill; J.R. Anderson, A.T. Corbett. 2. Learning by Explaining Examples to Oneself: A Computational Model; K. VanLehn, R.M. Jones. 3. Learning Schemas from Explanations in Practical Electronics; D.E. Kieras. 4. Statistical and Cognitive Models of Learning Through Instruction; S.P. Marshall. 5. The Interaction Between Konwledge and Practice in the Acquisition of Cognitive Skills; S. Ohlsson. 6. Correcting Imperfect Domain Theories: A Knowledge-Level Analysis; S.B. Huffman, D.J. Pearson, J.E. Laird. 7. A Cognitive Science Approach to Case-Based Planning; K.J.Hammond, C.M. Seifert. 8. Bias in Planning and Explanation-Based Learning; P.S. Rosenbloom, Soowon Lee, A. Unruh. 9. Knowledge Acquisition and Natural Language Processing; R. Wilensky. Index.

ISBN: 9780792392774
ISBN-10: 0792392779
Audience: Professional
Format: Hardcover
Language: English
Number Of Pages: 339
Published: December 2009
Publisher: Springer
Country of Publication: NL
Dimensions (cm): 24.77 x 16.51  x 2.54
Weight (kg): 0.79