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Titlebook: Universal Subgoaling and Chunking; The Automatic Genera John Laird,Paul Rosenbloom,Allen Newell Book 1986 Kluwer Academic Publishers 1986 a

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书目名称Universal Subgoaling and Chunking
副标题The Automatic Genera
编辑John Laird,Paul Rosenbloom,Allen Newell
视频video
丛书名称The Springer International Series in Engineering and Computer Science
图书封面Titlebook: Universal Subgoaling and Chunking; The Automatic Genera John Laird,Paul Rosenbloom,Allen Newell Book 1986 Kluwer Academic Publishers 1986 a
描述Rarely do research paths diverge and converge as neatly and productively as the paths exemplified by the two efforts contained in this book. The story behind these researches is worth recounting. The story, as far as I‘m concerned, starts back in the Fall of1976, when John Laird and Paul Rosenbloom, as new graduate students in computer science at Carnegie-Mellon University, joined the Instructible Production System (IPS) project (Rychener, Forgy, Langley, McDermott, Newell, Ramakrishna, 1977; Rychener & Newell, 1978). In those days, production systems were either small or special or both (Newell, 1973; Shortliffe, 1976). Mike Rychener had just completed his thesis (Rychener, 1976), showing how production systems could effectively and perspicuously program the full array of artificial intelligence (AI) systems, by creating versions of Studellt (done in an earlier study, Rychener 1975), EPAM, GPS, King-Pawn-King endgames, a toy-blocks problem solver, and a natural-language input system that connected to the blocks-world system.
出版日期Book 1986
关键词algorithms; artificial intelligence; control; intelligence; learning; memory; simulation
版次1
doihttps://doi.org/10.1007/978-1-4613-2277-1
isbn_softcover978-1-4612-9405-4
isbn_ebook978-1-4613-2277-1Series ISSN 0893-3405
issn_series 0893-3405
copyrightKluwer Academic Publishers 1986
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Introductionffective. A system is engaged in practice when it repeatedly performs one, or a set of similar, tasks. Recently, Newell and Rosenbloom (1981) brought together the evidence that there is a ubiquitous law — the . — that characterizes the improvements in human performance during practice. The law state
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Practice theory of learning — represents the third in a continuing series of studies of the effects that practice has on performance. These new results are built upon the foundation laid by the two earlier efforts. The first study established that practice curves follow . functions, and developed a macrothe
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Goal-Structured Modelsing curves produced during practice. In Chapter 3 we showed how stimulus-response compatibility tasks could be modeled by algorithms written in a simple procedural language called .. In this chapter, these two (until now unrelated) efforts are integrated into a single model, based on the concept of
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Discussionrations in the choice of a set of primitive algorithmic operators; (2) the rate of learning; (3) errors; (4) other reaction-time phenomena; (5) the relation of chunking to previous research on learning mechanisms; (6) the application of chunking to more complex tasks; and (7) the emergence of compli
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