Autonomous Search

Editors: Hamadi, Youssef, Monfroy, Eric, Saubion, Frédéric (Eds.)

  • The contributors are among the leading researchers in the areas of heuristics, optimization, evolutionary computing and constraints
  • The book will be of benefit to researchers, engineers and postgraduates in the areas of constraint programming, machine learning and evolutionary computing
  • This is the first book dedicated to this topic
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eBook $119.00
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  • ISBN 978-3-642-21434-9
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  • Download immediately after purchase
Hardcover $159.00
price for USA
  • ISBN 978-3-642-21433-2
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $159.00
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  • ISBN 978-3-642-44334-3
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this book

Decades of innovations in combinatorial problem solving have produced better and more complex algorithms. These new methods are better since they can solve larger problems and address new application domains. They are also more complex which means that they are hard to reproduce and often harder to fine-tune to the peculiarities of a given problem. This last point has created a paradox where efficient tools are out of reach of practitioners.

Autonomous search (AS) represents a new research field defined to precisely address the above challenge. Its major strength and originality consist in the fact that problem solvers can now perform self-improvement operations based on analysis of the performances of the solving process -- including short-term reactive reconfiguration and long-term improvement through self-analysis of the performance, offline tuning and online control, and adaptive control and supervised control. Autonomous search "crosses the chasm" and provides engineers and practitioners with systems that are able to autonomously self-tune their performance while effectively solving problems.

This is the first book dedicated to this topic, and it can be used as a reference for researchers, engineers, and postgraduates in the areas of constraint programming, machine learning, evolutionary computing, and feedback control theory. After the editors' introduction to autonomous search, the chapters are focused on tuning algorithm parameters, autonomous complete (tree-based) constraint solvers, autonomous control in metaheuristics and heuristics, and future autonomous solving paradigms.

Autonomous search (AS) represents a new research field defined to precisely address the above challenge. Its major strength and originality consist in the fact that problem solvers can now perform self-improvement operations based on analysis of the performances of the solving process -- including short-term reactive reconfiguration and long-term improvement through self-analysis of the performance, offline tuning and online control, and adaptive control and supervised control. Autonomous search "crosses the chasm" and provides engineers and practitioners with systems that are able to autonomously self-tune their performance while effectively solving problems.

This is the first book dedicated to this topic, and it can be used as a reference for researchers, engineers, and postgraduates in the areas of constraint programming, machine learning, evolutionary computing, and feedback control theory. After the editors' introduction to autonomous search, the chapters are focused on tuning algorithm parameters, autonomous complete (tree-based) constraint solvers, autonomous control in metaheuristics and heuristics, and future autonomous solving paradigms.

This is the first book dedicated to this topic, and it can be used as a reference for researchers, engineers, and postgraduates in the areas of constraint programming, machine learning, evolutionary computing, and feedback control theory. After the editors' introduction to autonomous search, the chapters are focused on tuning algorithm parameters, autonomous complete (tree-based) constraint solvers, autonomous control in metaheuristics and heuristics, and future autonomous solving paradigms.

This is the first book dedicated to this topic, and it can be used as a reference for researchers, engineers, and postgraduates in the areas of constraint programming, machine learning, evolutionary computing, and feedback control theory. After the editors' introduction to autonomous search, the chapters are focused on tuning algorithm parameters, autonomous complete (tree-based) constraint solvers, autonomous control in metaheuristics and heuristics, and future autonomous solving paradigms.

About the authors

Dr. Youssef Hamadi is the head of the Constraint Reasoning Group at Microsoft Research Cambridge, and his research interests include combinatorial optimization in alternative frameworks (parallel and distributed architectures); the application of machine learning to search; autonomous search; and parallel propositional satisfiability. Prof. Eric Monfroy is affiliated with both the Universidad Técnica Federico Santa María, Valparaíso, Chile and LINA, Université de Nantes, France; his research areas include heuristics, optimization, constraints, and search. Prof. Frédéric Saubion coheads the Metaheuristics, Optimization and Applications team at the Université d'Angers; his research topics include hybrid and adaptive evolutionary algorithms and applications of metaheuristics to various domains such as information retrieval, nonmonotonic reasoning and biology.

Table of contents (11 chapters)

  • An Introduction to Autonomous Search

    Hamadi, Youssef (et al.)

    Pages 1-11

  • Evolutionary Algorithm Parameters and Methods to Tune Them

    Eiben, A. E. (et al.)

    Pages 15-36

  • Automated Algorithm Configuration and Parameter Tuning

    Hoos, Holger H.

    Pages 37-71

  • Case-Based Reasoning for Autonomous Constraint Solving

    Bridge, Derek (et al.)

    Pages 73-95

  • Learning a Mixture of Search Heuristics

    Epstein, Susan L. (et al.)

    Pages 97-127

Buy this book

eBook $119.00
price for USA
  • ISBN 978-3-642-21434-9
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Download immediately after purchase
Hardcover $159.00
price for USA
  • ISBN 978-3-642-21433-2
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $159.00
price for USA
  • ISBN 978-3-642-44334-3
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Autonomous Search
Editors
  • Youssef Hamadi
  • Eric Monfroy
  • Frédéric Saubion
Copyright
2012
Publisher
Springer-Verlag Berlin Heidelberg
Copyright Holder
Springer-Verlag Berlin Heidelberg
eBook ISBN
978-3-642-21434-9
DOI
10.1007/978-3-642-21434-9
Hardcover ISBN
978-3-642-21433-2
Softcover ISBN
978-3-642-44334-3
Edition Number
1
Number of Pages
XVI, 308
Topics