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Generating Abstraction Hierarchies

Author: Craig A. Knoblock

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 179

ISBN-13: 1461531527

Generating Abstraction Hierarchies presents a completely automated approach to generating abstractions for problem solving. The abstractions are generated using a tractable, domain-independent algorithm whose only inputs are the definition of a problem space and the problem to be solved and whose output is an abstraction hierarchy that is tailored to the particular problem. The algorithm generates abstraction hierarchies that satisfy the `ordered monotonicity' property, which guarantees that the structure of an abstract solution is not changed in the process of refining it. An abstraction hierarchy with this property allows a problem to be decomposed such that the solution in an abstract space can be held invariant while the remaining parts of a problem are solved. The algorithm for generating abstractions is implemented in a system called ALPINE, which generates abstractions for a hierarchical version of the PRODIGY problem solver. Generating Abstraction Hierarchies formally defines this hierarchical problem solving method, shows that under certain assumptions this method can reduce the size of a search space from exponential to linear in the solution size, and describes the implementation of this method in PRODIGY. The abstractions generated by ALPINE are tested in multiple domains on large problem sets and are shown to produce shorter solutions with significantly less search than problem solving without using abstraction. Generating Abstraction Hierarchies will be of interest to researchers in machine learning, planning and problem reformation.

Generating Abstraction Hierarchies

Author: Craig Knoblock

Publisher: Springer Science & Business Media

Published: 1993-01-31

Total Pages: 194

ISBN-13: 9780792393108

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Generating Abstraction Hierarchies presents a completely automated approach to generating abstractions for problem solving. The abstractions are generated using a tractable, domain-independent algorithm whose only inputs are the definition of a problem space and the problem to be solved and whose output is an abstraction hierarchy that is tailored to the particular problem. The algorithm generates abstraction hierarchies that satisfy the `ordered monotonicity' property, which guarantees that the structure of an abstract solution is not changed in the process of refining it. An abstraction hierarchy with this property allows a problem to be decomposed such that the solution in an abstract space can be held invariant while the remaining parts of a problem are solved. The algorithm for generating abstractions is implemented in a system called ALPINE, which generates abstractions for a hierarchical version of the PRODIGY problem solver. Generating Abstraction Hierarchies formally defines this hierarchical problem solving method, shows that under certain assumptions this method can reduce the size of a search space from exponential to linear in the solution size, and describes the implementation of this method in PRODIGY. The abstractions generated by ALPINE are tested in multiple domains on large problem sets and are shown to produce shorter solutions with significantly less search than problem solving without using abstraction. Generating Abstraction Hierarchies will be of interest to researchers in machine learning, planning and problem reformation.

Multiple Abstraction Hierarchies for Mobile Robot Operation in Large Environments

Author: Cipriano Galindo

Publisher: Springer

Published: 2007-07-07

Total Pages: 184

ISBN-13: 354072690X

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This book focuses on the performance of mobile robots through the use of multi-hierarchical symbolic representations of the environment. To perform deliberative actions, a robot must possess some symbolic representation of its workspace, but representations of real environments can become so large that they must be conveniently arranged to facilitate and, in some cases, make possible their use. Practical solutions tested on real robots, for example a robotic wheelchair, are provided.

Artificial Intelligence Planning Systems

Author: James Hendler

Publisher: Elsevier

Published: 2014-06-28

Total Pages: 327

ISBN-13: 0080499449

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Artificial Intelligence Planning Systems documents the proceedings of the First International Conference on AI Planning Systems held in College Park, Maryland on June 15-17, 1992. This book discusses the abstract probabilistic modeling of action; building symbolic primitives with continuous control routines; and systematic adaptation for case-based planning. The analysis of ABSTRIPS; conditional nonlinear planning; and building plans to monitor and exploit open-loop and closed-loop dynamics are also elaborated. This text likewise covers the modular utility representation for decision-theoretic planning; reaction and reflection in tetris; and planning in intelligent sensor fusion. Other topics include the resource-bounded adaptive agent, critical look at Knoblock's hierarchy mechanism, and traffic laws for mobile robots. This publication is beneficial to students and researchers conducting work on AI planning systems.

Artificial Intelligence and Symbolic Computation

Author: Bruno Buchberger

Publisher: Springer

Published: 2004-12-13

Total Pages: 295

ISBN-13: 3540302107

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AISC 2004, the 7th International Conference on Artificial Intelligence and Symbolic Computation, was the latest in the series of specialized biennial conferences founded in 1992 by Jacques Calmet of the Universitat ̈ Karlsruhe and John Campbell of University College London with the initial title Artificial Intelligence and Symbolic Mathematical Computing (AISMC).The M disappeared from the title between the 1996 and 1998 conferences. As the editors of the AISC 1998 proceedings said, the organizers of the current meeting decided to drop the adjective 'mathematical' and to emphasize that the conference is concerned with all aspects of symbolic computation in AI: mathematical foundations, implementations, and applications, including applications in industry and academia. This remains the intended profile of the series, and will figure in the call for papers for AISC 2006,which is intended to take place in China. The distribution of papers in the present volume over all the areas of AISC happens to be rather noticeably mathematical, an effect that emerged because we were concerned to select the best relevant papers that were offered to us in 2004, irrespective of their particular topics; hence the title on the cover. Nevertheless, we encourage researchers over the entire spectrum of AISC, as expressed by the 1998 quotation above,to be in touch with us about their interests and the possibility of eventual submission of papers on their work for the next conference in the series. The papers in the present volume are evidence of the health of the field of AISC. Additionally, there are two reasons for optimism about the continuation of this situation.

ECAI 2004

Author: Ramon López de Mántaras

Publisher: IOS Press

Published: 2004

Total Pages: 1184

ISBN-13: 9781586034528

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This is the Golden Age for Artificial Intelligence. The world is becoming increasingly automated and wired together. This also increases the opportunities for AI to help people and commerce. Almost every sub field of AI had now been used in substantial applications. Some of the fields highlighted in this publication are: CBR Technology; Model Based Systems; Data Mining and Natural Language Techniques. Not only does this publication show the activities, capabilities and accomplishments of the sub fields, it also focuses on what is happening across the field as a whole.