Instance Specific Algorithm Configuration
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Instance Specific Algorithm Configuration
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Author : Yuri Malitsky
language : en
Publisher: Springer
Release Date : 2014-11-20
Instance Specific Algorithm Configuration written by Yuri Malitsky and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-20 with Computers categories.
This book presents a modular and expandable technique in the rapidly emerging research area of automatic configuration and selection of the best algorithm for the instance at hand. The author presents the basic model behind ISAC and then details a number of modifications and practical applications. In particular, he addresses automated feature generation, offline algorithm configuration for portfolio generation, algorithm selection, adaptive solvers, online tuning, and parallelization. The author's related thesis was honorably mentioned (runner-up) for the ACP Dissertation Award in 2014, and this book includes some expanded sections and notes on recent developments. Additionally, the techniques described in this book have been successfully applied to a number of solvers competing in the SAT and MaxSAT International Competitions, winning a total of 18 gold medals between 2011 and 2014. The book will be of interest to researchers and practitioners in artificial intelligence, in particular in the area of machine learning and constraint programming.
Generic Instance Specific Automated Parameter Tuning Framework
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Author :
language : en
Publisher:
Release Date : 2014
Generic Instance Specific Automated Parameter Tuning Framework written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with Algorithms categories.
"Meta-heuristic algorithms play an important role in solving combinatorial optimization problems (COP) in many practical applications. The caveat is that the performance of these meta-heuristic algorithms is highly dependent on their parameter configuration which controls the algorithm behavior. Selecting the best parameter configuration is often a difficult, tedious and unsatisfying task. This thesis studies the problem of automating the selection of good parameter configurations..." -- Author's abstract.
Learning And Intelligent Optimization
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Author : Paola Festa
language : en
Publisher: Springer
Release Date : 2016-11-29
Learning And Intelligent Optimization written by Paola Festa and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-29 with Computers categories.
This book constitutes the thoroughly refereed post-conference proceedings of the 10th International Conference on Learning and Optimization, LION 10, which was held on Ischia, Italy, in May/June 2016. The 14 full papers presented together with 9 short papers and 2 GENOPT papers were carefully reviewed and selected from 47 submissions. The papers address all fields between machine learning, artificial intelligence, mathematical programming and algorithms for hard optimization problems. Special focus is given to new ideas and methods; challenges and opportunities in various application areas; general trends, and specific developments.
Handbook Of Satisfiability
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Author : A. Biere
language : en
Publisher: IOS Press
Release Date : 2021-05-05
Handbook Of Satisfiability written by A. Biere and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-05 with Computers categories.
Propositional logic has been recognized throughout the centuries as one of the cornerstones of reasoning in philosophy and mathematics. Over time, its formalization into Boolean algebra was accompanied by the recognition that a wide range of combinatorial problems can be expressed as propositional satisfiability (SAT) problems. Because of this dual role, SAT developed into a mature, multi-faceted scientific discipline, and from the earliest days of computing a search was underway to discover how to solve SAT problems in an automated fashion. This book, the Handbook of Satisfiability, is the second, updated and revised edition of the book first published in 2009 under the same name. The handbook aims to capture the full breadth and depth of SAT and to bring together significant progress and advances in automated solving. Topics covered span practical and theoretical research on SAT and its applications and include search algorithms, heuristics, analysis of algorithms, hard instances, randomized formulae, problem encodings, industrial applications, solvers, simplifiers, tools, case studies and empirical results. SAT is interpreted in a broad sense, so as well as propositional satisfiability, there are chapters covering the domain of quantified Boolean formulae (QBF), constraints programming techniques (CSP) for word-level problems and their propositional encoding, and satisfiability modulo theories (SMT). An extensive bibliography completes each chapter. This second edition of the handbook will be of interest to researchers, graduate students, final-year undergraduates, and practitioners using or contributing to SAT, and will provide both an inspiration and a rich resource for their work. Edmund Clarke, 2007 ACM Turing Award Recipient: "SAT solving is a key technology for 21st century computer science." Donald Knuth, 1974 ACM Turing Award Recipient: "SAT is evidently a killer app, because it is key to the solution of so many other problems." Stephen Cook, 1982 ACM Turing Award Recipient: "The SAT problem is at the core of arguably the most fundamental question in computer science: What makes a problem hard?"
Autonomous Search
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Author : Youssef Hamadi
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-01-05
Autonomous Search written by Youssef Hamadi and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-01-05 with Computers categories.
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.
Learning And Intelligent Optimization
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Author : Dimitris E. Simos
language : en
Publisher: Springer Nature
Release Date : 2021-12-08
Learning And Intelligent Optimization written by Dimitris E. Simos and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-08 with Mathematics categories.
This book constitutes the refereed post-conference proceedings on Learning and Intelligent Optimization, LION 15, held in Athens, Greece, in June 2021. The 30 full papers presented have been carefully reviewed and selected from 35 submissions. LION deals with designing and engineering ways of "learning" about the performance of different techniques, and ways of using past experience about the algorithm behavior to improve performance in the future. Intelligent learning schemes for mining the knowledge obtained online or offline can improve the algorithm design process and simplify the applications of high-performance optimization methods. Combinations of different algorithms can further improve the robustness and performance of the individual components.
Handbook Of Parallel Constraint Reasoning
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Author : Youssef Hamadi
language : en
Publisher: Springer
Release Date : 2018-04-05
Handbook Of Parallel Constraint Reasoning written by Youssef Hamadi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-05 with Computers categories.
This is the first book presenting a broad overview of parallelism in constraint-based reasoning formalisms. In recent years, an increasing number of contributions have been made on scaling constraint reasoning thanks to parallel architectures. The goal in this book is to overview these achievements in a concise way, assuming the reader is familiar with the classical, sequential background. It presents work demonstrating the use of multiple resources from single machine multi-core and GPU-based computations to very large scale distributed execution platforms up to 80,000 processing units. The contributions in the book cover the most important and recent contributions in parallel propositional satisfiability (SAT), maximum satisfiability (MaxSAT), quantified Boolean formulas (QBF), satisfiability modulo theory (SMT), theorem proving (TP), answer set programming (ASP), mixed integer linear programming (MILP), constraint programming (CP), stochastic local search (SLS), optimal path finding with A*, model checking for linear-time temporal logic (MC/LTL), binary decision diagrams (BDD), and model-based diagnosis (MBD). The book is suitable for researchers, graduate students, advanced undergraduates, and practitioners who wish to learn about the state of the art in parallel constraint reasoning.
Theory And Applications Of Satisfiability Testing Sat 2021
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Author : Chu-Min Li
language : en
Publisher: Springer Nature
Release Date : 2021-07-01
Theory And Applications Of Satisfiability Testing Sat 2021 written by Chu-Min Li and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-01 with Computers categories.
This book constitutes the proceedings of the 24th International Conference on Theory and Applications of Satisfiability Testing, SAT 2021, which took place in Barcelona, Spain, in July 2021. The 37 full papers presented in this volume were carefully reviewed and selected from 73 submissions. They deal with theory and applications of the propositional satisfiability problem, broadly construed. Aside from plain propositional satisfiability, the scope of the meeting includes Boolean optimization, including MaxSAT and pseudo-Boolean (PB) constraints, quantified Boolean formulas (QBF), satisfiability modulo theories (SMT), and constraint programming (CP) for problems with clear connections to Boolean reasoning.
Learning And Intelligent Optimization
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Author : Clarisse Dhaenens
language : en
Publisher: Springer
Release Date : 2015-06-18
Learning And Intelligent Optimization written by Clarisse Dhaenens and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-18 with Computers categories.
This book constitutes the thoroughly refereed post-conference proceedings of the 9th International Conference on Learning and Optimization, LION 9, which was held in Lille, France, in January 2015. The 31 contributions presented were carefully reviewed and selected for inclusion in this book. The papers address all fields between machine learning, artificial intelligence, mathematical programming and algorithms for hard optimization problems. Special focus is given to algorithm selection and configuration, learning, fitness landscape, applications, dynamic optimization, multi-objective, max-clique problems, bayesian optimization and global optimization, data mining and - in a special session - also on dynamic optimization.
Machine Learning And Knowledge Discovery In Databases
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Author : Hendrik Blockeel
language : en
Publisher: Springer
Release Date : 2013-08-28
Machine Learning And Knowledge Discovery In Databases written by Hendrik Blockeel and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-08-28 with Computers categories.
This three-volume set LNAI 8188, 8189 and 8190 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2013, held in Prague, Czech Republic, in September 2013. The 111 revised research papers presented together with 5 invited talks were carefully reviewed and selected from 447 submissions. The papers are organized in topical sections on reinforcement learning; Markov decision processes; active learning and optimization; learning from sequences; time series and spatio-temporal data; data streams; graphs and networks; social network analysis; natural language processing and information extraction; ranking and recommender systems; matrix and tensor analysis; structured output prediction, multi-label and multi-task learning; transfer learning; bayesian learning; graphical models; nearest-neighbor methods; ensembles; statistical learning; semi-supervised learning; unsupervised learning; subgroup discovery, outlier detection and anomaly detection; privacy and security; evaluation; applications; and medical applications.