Stochastic Local Search

Author: Holger H. Hoos
Publisher: Morgan Kaufmann
ISBN: 1558608729
Format: PDF, Mobi
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Stochastic local search (SLS) algorithms are among the most prominent and successful techniques for solving computationally difficult problems. Offering a systematic treatment of SLS algorithms, this book examines the general concepts and specific instances of SLS algorithms and considers their development, analysis and application.

Engineering Stochastic Local Search Algorithms Designing Implementing and Analyzing Effective Heuristics

Author: Thomas Stützle
Publisher: Springer
ISBN: 3642037518
Format: PDF, Kindle
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Stochastic local search (SLS) algorithms are established tools for the solution of computationally hard problems arising in computer science, business adm- istration, engineering, biology, and various other disciplines. To a large extent, their success is due to their conceptual simplicity, broad applicability and high performance for many important problems studied in academia and enco- tered in real-world applications. SLS methods include a wide spectrum of te- niques, ranging from constructive search procedures and iterative improvement algorithms to more complex SLS methods, such as ant colony optimization, evolutionary computation, iterated local search, memetic algorithms, simulated annealing, tabu search, and variable neighborhood search. Historically, the development of e?ective SLS algorithms has been guided to a large extent by experience and intuition. In recent years, it has become - creasingly evident that success with SLS algorithms depends not merely on the adoption and e?cient implementation of the most appropriate SLS technique for a given problem, but also on the mastery of a more complex algorithm - gineering process. Challenges in SLS algorithm development arise partly from the complexity of the problems being tackled and in part from the many - grees of freedom researchers and practitioners encounter when developing SLS algorithms. Crucial aspects in the SLS algorithm development comprise al- rithm design, empirical analysis techniques, problem-speci?c background, and background knowledge in several key disciplines and areas, including computer science, operations research, arti?cial intelligence, and statistics.

Handbook of Constraint Programming

Author: Francesca Rossi
Publisher: Elsevier
ISBN: 9780080463803
Format: PDF, Mobi
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Constraint programming is a powerful paradigm for solving combinatorial search problems that draws on a wide range of techniques from artificial intelligence, computer science, databases, programming languages, and operations research. Constraint programming is currently applied with success to many domains, such as scheduling, planning, vehicle routing, configuration, networks, and bioinformatics. The aim of this handbook is to capture the full breadth and depth of the constraint programming field and to be encyclopedic in its scope and coverage. While there are several excellent books on constraint programming, such books necessarily focus on the main notions and techniques and cannot cover also extensions, applications, and languages. The handbook gives a reasonably complete coverage of all these lines of work, based on constraint programming, so that a reader can have a rather precise idea of the whole field and its potential. Of course each line of work is dealt with in a survey-like style, where some details may be neglected in favor of coverage. However, the extensive bibliography of each chapter will help the interested readers to find suitable sources for the missing details. Each chapter of the handbook is intended to be a self-contained survey of a topic, and is written by one or more authors who are leading researchers in the area. The intended audience of the handbook is researchers, graduate students, higher-year undergraduates and practitioners who wish to learn about the state-of-the-art in constraint programming. No prior knowledge about the field is necessary to be able to read the chapters and gather useful knowledge. Researchers from other fields should find in this handbook an effective way to learn about constraint programming and to possibly use some of the constraint programming concepts and techniques in their work, thus providing a means for a fruitful cross-fertilization among different research areas. The handbook is organized in two parts. The first part covers the basic foundations of constraint programming, including the history, the notion of constraint propagation, basic search methods, global constraints, tractability and computational complexity, and important issues in modeling a problem as a constraint problem. The second part covers constraint languages and solver, several useful extensions to the basic framework (such as interval constraints, structured domains, and distributed CSPs), and successful application areas for constraint programming. - Covers the whole field of constraint programming - Survey-style chapters - Five chapters on applications

Illustrating Evolutionary Computation with Mathematica

Author: Christian Jacob
Publisher: Morgan Kaufmann
ISBN: 1558606378
Format: PDF, ePub, Docs
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An essential capacity of intelligence is the ability to learn. An artificially intelligent system that could learn would not have to be programmed for every eventuality; it could adapt to its changing environment and conditions just as biological systems do. Illustrating Evolutionary Computation with Mathematica introduces evolutionary computation to the technically savvy reader who wishes to explore this fascinating and increasingly important field. Unique among books on evolutionary computation, the book also explores the application of evolution to developmental processes in nature, such as the growth processes in cells and plants. If you are a newcomer to the evolutionary computation field, an engineer, a programmer, or even a biologist wanting to learn how to model the evolution and coevolution of plants, this book will provide you with a visually rich and engaging account of this complex subject. * Introduces the major mechanisms of biological evolution. * Demonstrates many fascinating aspects of evolution in nature with simple, yet illustrative examples. * Explains each of the major branches of evolutionary computation: genetic algorithms, genetic programming, evolutionary programming, and evolution strategies. * Demonstrates the programming of computers by evolutionary principles using Evolvica, a genetic programming system designed by the author. * Shows in detail how to evolve developmental programs modeled by cellular automata and Lindenmayer systems. * Provides Mathematica notebooks on the Web that include all the programs in the book and supporting animations, movies, and graphics.

Artificial Intelligence Methodology Systems and Applications

Author: Jérôme Euzenat
Publisher: Springer
ISBN: 3540409319
Format: PDF, ePub, Mobi
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This book constitutes the refereed proceedings of the 12th International Conference on Artificial Intelligence: Methodology, Systems, and Applications, AIMSA 2006. The 28 revised full papers presented together with the abstracts of 2 invited lectures were carefully reviewed and selected from 81 submissions. The papers are organized in topical sections on agents, constraints and optimization, user concerns, decision support, models and ontologies, machine learning, ontology manipulation, natural language processing, and applications.

Constraint Processing

Author: Rina Dechter
Publisher: Morgan Kaufmann
ISBN: 1558608907
Format: PDF, Docs
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Constraint satisfaction is a simple but powerful tool. Constraints identify the impossible and reduce the realm of possibilities to effectively focus on the possible, allowing for a natural declarative formulation of what must be satisfied, without expressing how. The field of constraint reasoning has matured over the last three decades with contributions from a diverse community of researchers in artificial intelligence, databases and programming languages, operations research, management science, and applied mathematics. Today, constraint problems are used to model cognitive tasks in vision, language comprehension, default reasoning, diagnosis, scheduling, temporal and spatial reasoning. In Constraint Processing, Rina Dechter, synthesizes these contributions, along with her own significant work, to provide the first comprehensive examination of the theory that underlies constraint processing algorithms. Throughout, she focuses on fundamental tools and principles, emphasizing the representation and analysis of algorithms. ·Examines the basic practical aspects of each topic and then tackles more advanced issues, including current research challenges ·Builds the reader's understanding with definitions, examples, theory, algorithms and complexity analysis ·Synthesizes three decades of researchers work on constraint processing in AI, databases and programming languages, operations research, management science, and applied mathematics

Blondie24

Author: David B. Fogel
Publisher: Morgan Kaufmann
ISBN: 9781558607835
Format: PDF, ePub, Docs
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"Blondie24 tells the story of a computer that taught itself to play checkers far better than its creators ever could by emulating the principles of Darwinian evolution and discovering innovative ways to approach the game. In this year of 2001, as we remember Arthur C. Clarke's predictions, David Fogel dramatically demonstrates how evolutionary computation may enable humans to create a thinking machine far more readily than the techniques traditionally used in the study of artificial intelligence."--BOOK JACKET.

Swarm Intelligence

Author: James Kennedy
Publisher: Morgan Kaufmann
ISBN: 9781558605954
Format: PDF, ePub, Docs
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A scholarly text on swarm intelligence that argues that intelligent human cognition derives from the interactions of individuals in a social world.

Knowledge Representation and Reasoning

Author: Ronald J. Brachman
Publisher: Morgan Kaufmann
ISBN: 9781558609327
Format: PDF, Mobi
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Knowledge representation is at the very core of a radical idea for understanding intelligence. This book talks about the central concepts of knowledge representation developed over the years. It is suitable for researchers and practitioners in database management, information retrieval, object-oriented systems and artificial intelligence.

AI 2005 Advances in Artificial Intelligence

Author: Shichao Zhang
Publisher: Springer
ISBN:
Format: PDF, ePub, Docs
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This book constitutes the refereed proceedings of the 18th Australian Joint Conference on Artificial Intelligence, AI 2005, held in Sydney, Australia in December 2005. The 77 revised full papers and 119 revised short papers presented together with the abstracts of 3 keynote speeches were carefully reviewed and selected from 535 submissions. The papers are catgorized in three broad sections, namely: AI foundations and technologies, computational intelligence, and AI in specialized domains. Particular topics addressed by the papers are logic and reasoning, machine learning, game theory, robotic technology, data mining, neural networks, fuzzy theory and algorithms, evolutionary computing, Web intelligence, decision making, pattern recognition, agent technology, and AI applications.