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Titlebook: Dynamic Flexible Constraint Satisfaction and its Application to AI Planning; Ian Miguel Book 2004 Springer Verlag London Limited 2004 Cons

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發(fā)表于 2025-3-21 19:52:27 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Dynamic Flexible Constraint Satisfaction and its Application to AI Planning
編輯Ian Miguel
視頻videohttp://file.papertrans.cn/284/283592/283592.mp4
概述Methods are developed which, for the first time, are able to solve problems which both contain a dynamic component and are open to compromise if a ‘perfect’ solution does not exist.Classical artificia
叢書名稱Distinguished Dissertations
圖書封面Titlebook: Dynamic Flexible Constraint Satisfaction and its Application to AI Planning; Ian Miguel Book 2004 Springer Verlag London Limited 2004 Cons
描述First, I would like to thank my principal supervisor Dr Qiang Shen for all his help, advice and friendship throughout. Many thanks also to my second supervisor Dr Peter Jarvis for his enthusiasm, help and friendship. I would also like to thank the other members of the Approximate and Qualitative Reasoning group at Edinburgh who have also helped and inspired me. This project has been funded by an EPSRC studentship, award num- ber 97305803. I would like, therefore, to extend my gratitude to EPSRC for supporting this work. Many thanks to the staff at Edinburgh University for all their help and support and for promptly fixing any technical problems that I have had . My whole family have been both encouraging and supportive throughout the completion of this book, for which I am forever indebted. York, April 2003 Ian Miguel Contents List of Figures XV 1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1. 1 Solving Classical CSPs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1. 2 Applicat ions of Classical CSP . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1. 3 Limitations of Classical CSP . . . .
出版日期Book 2004
關(guān)鍵詞Constraint Satisfaction; Extension; algorithms; artificial intelligence; complexity; constraint satisfact
版次1
doihttps://doi.org/10.1007/978-0-85729-378-7
isbn_softcover978-1-4471-1048-4
isbn_ebook978-0-85729-378-7
copyrightSpringer Verlag London Limited 2004
The information of publication is updating

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沙發(fā)
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FGP: Experimental Results,e the overhead incurred by searching for a range of plans. In addition, the utility of the limited graph expansion and satisfaction propagation techniques described in Sections 7.3.3 and 7.3.4 respectively are examined with respect to the test suite.
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Dynamic CSP in Domain-independent AI Planning,tisfaction problem enables a gain in efficiency via the use of the dedicated search algorithms available in this field [82]. This chapter continues in this vein, presenting a novel technique which exploits (restriction/relaxation-based) dynamic CSP in order to further improve planner performance.
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發(fā)表于 2025-3-22 15:55:34 | 只看該作者
Evidenzbasierte P?dagogik – ein Déjà-vu?to carry only one passenger, although a second can be carried in an emergency; the maths class must be scheduled between 9 and 11am, but it may be moved to the afternoon later in the term. It is this generality and simplicity of structure which underly the ubiquity of the constraint-based representation in Artificial Intelligence.
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發(fā)表于 2025-3-22 20:22:34 | 只看該作者
Einleitung: Wirtschaftliche Rationalit?te the overhead incurred by searching for a range of plans. In addition, the utility of the limited graph expansion and satisfaction propagation techniques described in Sections 7.3.3 and 7.3.4 respectively are examined with respect to the test suite.
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發(fā)表于 2025-3-23 08:53:28 | 只看該作者
Evidenzbasierte P?dagogik – ein Déjà-vu?tisfaction problem enables a gain in efficiency via the use of the dedicated search algorithms available in this field [82]. This chapter continues in this vein, presenting a novel technique which exploits (restriction/relaxation-based) dynamic CSP in order to further improve planner performance.
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