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Instance Specific Algorithm Configuration
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Book Synopsis Instance-Specific Algorithm Configuration by : Yuri Malitsky
Download or read book Instance-Specific Algorithm Configuration written by Yuri Malitsky and published by Springer. This book was released on 2014-11-20 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Autonomous Search by : Youssef Hamadi
Download or read book Autonomous Search written by Youssef Hamadi and published by Springer Science & Business Media. This book was released on 2012-01-05 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems by : Nicolas Beldiceanu
Download or read book Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems written by Nicolas Beldiceanu and published by Springer. This book was released on 2012-05-15 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 9th International Conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems, CPAIOR 2012, held in Nantes, France, in May/June 2012. The 26 revised full papers presented were carefully reviewed and selected from 64 submissions. The papers are focused on both theoretical and practical, application-oriented issues in combinatorial optimization and feature current research with a special focus on inference and relaxation methods, integration methods, modeling methods, innovative applications of CP/AI/OR techniques, and implementation of CP/AI/OR techniques and optimization systems.
Book Synopsis Automated Design of Machine Learning and Search Algorithms by : Nelishia Pillay
Download or read book Automated Design of Machine Learning and Search Algorithms written by Nelishia Pillay and published by Springer Nature. This book was released on 2021-07-28 with total page 187 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent advances in automated machine learning (AutoML) and automated algorithm design and indicates the future directions in this fast-developing area. Methods have been developed to automate the design of neural networks, heuristics and metaheuristics using techniques such as metaheuristics, statistical techniques, machine learning and hyper-heuristics. The book first defines the field of automated design, distinguishing it from the similar but different topics of automated algorithm configuration and automated algorithm selection. The chapters report on the current state of the art by experts in the field and include reviews of AutoML and automated design of search, theoretical analyses of automated algorithm design, automated design of control software for robot swarms, and overfitting as a benchmark and design tool. Also covered are automated generation of constructive and perturbative low-level heuristics, selection hyper-heuristics for automated design, automated design of deep-learning approaches using hyper-heuristics, genetic programming hyper-heuristics with transfer knowledge and automated design of classification algorithms. The book concludes by examining future research directions of this rapidly evolving field. The information presented here will especially interest researchers and practitioners in the fields of artificial intelligence, computational intelligence, evolutionary computation and optimisation.
Book Synopsis Handbook of Satisfiability by : A. Biere
Download or read book Handbook of Satisfiability written by A. Biere and published by IOS Press. This book was released on 2021-05-05 with total page 1486 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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?"
Book Synopsis Learning and Intelligent Optimization by : Paola Festa
Download or read book Learning and Intelligent Optimization written by Paola Festa and published by Springer. This book was released on 2016-11-29 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Learning and Intelligent Optimization by : Dimitris E. Simos
Download or read book Learning and Intelligent Optimization written by Dimitris E. Simos and published by Springer Nature. This book was released on 2021-12-08 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Handbook of Parallel Constraint Reasoning by : Youssef Hamadi
Download or read book Handbook of Parallel Constraint Reasoning written by Youssef Hamadi and published by Springer. This book was released on 2018-04-05 with total page 687 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Theory and Applications of Satisfiability Testing – SAT 2021 by : Chu-Min Li
Download or read book Theory and Applications of Satisfiability Testing – SAT 2021 written by Chu-Min Li and published by Springer Nature. This book was released on 2021-07-01 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Learning and Intelligent Optimization by : Clarisse Dhaenens
Download or read book Learning and Intelligent Optimization written by Clarisse Dhaenens and published by Springer. This book was released on 2015-06-18 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Machine Learning and Knowledge Discovery in Databases by : Hendrik Blockeel
Download or read book Machine Learning and Knowledge Discovery in Databases written by Hendrik Blockeel and published by Springer. This book was released on 2013-08-28 with total page 731 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Proceedings of SAI Intelligent Systems Conference (IntelliSys) 2016 by : Yaxin Bi
Download or read book Proceedings of SAI Intelligent Systems Conference (IntelliSys) 2016 written by Yaxin Bi and published by Springer. This book was released on 2017-08-19 with total page 1163 pages. Available in PDF, EPUB and Kindle. Book excerpt: These proceedings of the SAI Intelligent Systems Conference 2016 (IntelliSys 2016) offer a remarkable collection of chapters on a wide range of topics in intelligent systems, artificial intelligence and their applications to the real world. Authors hailing from 56 countries on 5 continents submitted 404 papers to the conference, attesting to the global importance of the conference’s themes. After being reviewed, 222 papers were accepted for presentation, and 168 were ultimately selected for these proceedings. Each has been reviewed on the basis of its originality, novelty and rigorousness. The papers not only present state-of-the-art methods and valuable experience from researchers in the related research areas; they also outline the field’s future development.
Book Synopsis Learning and Intelligent Optimization by : Youssef Hamadi
Download or read book Learning and Intelligent Optimization written by Youssef Hamadi and published by Springer. This book was released on 2012-10-01 with total page 533 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-conference proceedings of the 6th International Conference on Learning and Intelligent Optimization, LION 6, held in Paris, France, in January 2012. The 23 long and 30 short revised papers were carefully reviewed and selected from a total of 99 submissions. The papers focus on the intersections and uncharted territories between machine learning, artificial intelligence, mathematical programming and algorithms for hard optimization problems. In addition to the paper contributions the conference also included 3 invited speakers, who presented forefront research results and frontiers, and 3 tutorial talks, which were crucial in bringing together the different components of LION community.
Book Synopsis Learning and Intelligent Optimization by : Roberto Battiti
Download or read book Learning and Intelligent Optimization written by Roberto Battiti and published by Springer. This book was released on 2018-12-31 with total page 487 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-conference proceedings of the 12th International Conference on Learning and Intelligent Optimization, LION 12, held in Kalamata, Greece, in June 2018. The 28 full papers and 12 short papers presented have been carefully reviewed and selected from 62 submissions. The papers explore the advanced research developments in such interconnected fields as mathematical programming, global optimization, machine learning, and artificial intelligence. Special focus is given to advanced ideas, technologies, methods, and applications in optimization and machine learning.
Book Synopsis Tools and Algorithms for the Construction and Analysis of Systems by : Jan Friso Groote
Download or read book Tools and Algorithms for the Construction and Analysis of Systems written by Jan Friso Groote and published by Springer Nature. This book was released on 2021-03-22 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access two-volume set constitutes the proceedings of the 27th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2021, which was held during March 27 – April 1, 2021, as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2021. The conference was planned to take place in Luxembourg and changed to an online format due to the COVID-19 pandemic. The total of 41 full papers presented in the proceedings was carefully reviewed and selected from 141 submissions. The volume also contains 7 tool papers; 6 Tool Demo papers, 9 SV-Comp Competition Papers. The papers are organized in topical sections as follows: Part I: Game Theory; SMT Verification; Probabilities; Timed Systems; Neural Networks; Analysis of Network Communication. Part II: Verification Techniques (not SMT); Case Studies; Proof Generation/Validation; Tool Papers; Tool Demo Papers; SV-Comp Tool Competition Papers.
Book Synopsis Logic-Based Program Synthesis and Transformation by : Moreno Falaschi
Download or read book Logic-Based Program Synthesis and Transformation written by Moreno Falaschi and published by Springer. This book was released on 2015-12-16 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-conference proceedings of the 25th International Symposium on Logic-Based Program Synthesis and Transformation, LOPSTR 2015, held in Siena, Italy, in July 2015. The 21 revised full papers presented together with 3 invited talks were carefully reviewed and selected from 30 submissions. The aim of the LOPSTR series is to stimulate and promote international research and collaboration on logic-based program development. LOPSTR is open to contributions in all aspects of logic-based program development, all stages of the software life cycle, and issues of both programming-in-the-small and programming-in-the-large.
Book Synopsis Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems by : Carla Gomes
Download or read book Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems written by Carla Gomes and published by Springer. This book was released on 2013-04-11 with total page 403 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is a compilation of the research program of the 10th International Conference on the Integration of Artificial Intelligence (AI) and Operations Research (OR) Techniques in Constraint Programming, CPAIOR 2013, held at Yorktown Heights, NY, USA, in May 2013. This volume contains 20 full papers and 11 short papers that were carefully reviewed and selected from 71 submissions. The papers focus on new techniques or applications in the intersection of constraint programming (CP), artificial intelligence (AI) and operations research (OR).
