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Titlebook: Knowledge Acquisition for Expert Systems; A Practical Handbook Alison L. Kidd Book 1987 Plenum Press, New York 1987 Action.algorithms.compu

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书目名称Knowledge Acquisition for Expert Systems
副标题A Practical Handbook
编辑Alison L. Kidd
视频video
图书封面Titlebook: Knowledge Acquisition for Expert Systems; A Practical Handbook Alison L. Kidd Book 1987 Plenum Press, New York 1987 Action.algorithms.compu
描述Building an expert system involves eliciting, analyzing, and interpreting the knowledge that a human expert uses when solving problems. Expe­ rience has shown that this process of "knowledge acquisition" is both difficult and time consuming and is often a major bottleneck in the production of expert systems. Unfortunately, an adequate theoretical basis for knowledge acquisition has not yet been established. This re­ quires a classification of knowledge domains and problem-solving tasks and an improved understanding of the relationship between knowledge structures in human and machine. In the meantime, expert system builders need access to information about the techniques currently being employed and their effectiveness in different applications. The aim of this book, therefore, is to draw on the experience of AI scientists, cognitive psychologists, and knowledge engineers in discussing particular acquisition techniques and providing practical advice on their application. Each chapter provides a detailed description of a particular technique or methodology applied within a selected task domain. The relative strengths and weaknesses of the tech­ nique are summarized at the end of eac
出版日期Book 1987
关键词Action; algorithms; computer; performance; simulation; technology; time
版次1
doihttps://doi.org/10.1007/978-1-4613-1823-1
isbn_softcover978-1-4612-9019-3
isbn_ebook978-1-4613-1823-1
copyrightPlenum Press, New York 1987
The information of publication is updating

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发表于 2025-3-21 23:01:12 | 显示全部楼层
Alison L. Kidduse of public domain computer programs for geometric algebra...The modern framework for geometric computing highlighted will be of great use for communities working on image processing, computer vision, artificial intelligence, neural networks, neuroscience, robotics, control engineering, human and robot interfaces, haptics and humanoids..
发表于 2025-3-22 04:03:54 | 显示全部楼层
Joost Breuker,Bob Wielingause of public domain computer programs for geometric algebra...The modern framework for geometric computing highlighted will be of great use for communities working on image processing, computer vision, artificial intelligence, neural networks, neuroscience, robotics, control engineering, human and robot interfaces, haptics and humanoids..
发表于 2025-3-22 06:27:53 | 显示全部楼层
Benjamin Kuipers,Jerome P. Kassireruse of public domain computer programs for geometric algebra...The modern framework for geometric computing highlighted will be of great use for communities working on image processing, computer vision, artificial intelligence, neural networks, neuroscience, robotics, control engineering, human and robot interfaces, haptics and humanoids..
发表于 2025-3-22 09:46:01 | 显示全部楼层
John Fox,Christopher D. Myers,Melvyn F. Greaves,Susan Pegramuse of public domain computer programs for geometric algebra...The modern framework for geometric computing highlighted will be of great use for communities working on image processing, computer vision, artificial intelligence, neural networks, neuroscience, robotics, control engineering, human and robot interfaces, haptics and humanoids..
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Mildred L. G. Shaw,Brian R. Gainesuse of public domain computer programs for geometric algebra...The modern framework for geometric computing highlighted will be of great use for communities working on image processing, computer vision, artificial intelligence, neural networks, neuroscience, robotics, control engineering, human and robot interfaces, haptics and humanoids..
发表于 2025-3-23 00:02:40 | 显示全部楼层
John G. Gammackuse of public domain computer programs for geometric algebra...The modern framework for geometric computing highlighted will be of great use for communities working on image processing, computer vision, artificial intelligence, neural networks, neuroscience, robotics, control engineering, human and robot interfaces, haptics and humanoids..
发表于 2025-3-23 04:48:02 | 显示全部楼层
Anna Hartwer for dealing with such complicated signal processing [60]. In a stimulating series of articles, Pellionisz and Llinàs [77, 78] claim that the formalization of geometrical representation seems to be a dual process involving the expression of extrinsic physical cues built by intrinsic central nervo
发表于 2025-3-23 08:42:55 | 显示全部楼层
utilized projective depth [96, 102], projective invariants [23], and factorization methods [81, 105, 107] (factorization methods incorporate projective depth calculations). We compute projective depth using projective invariants, which depend on the use of the fundamental matrix or trifocal tensor.
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