Pattern Based Constraint Satisfaction And Logic Puzzles
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Pattern-Based Constraint Satisfaction and Logic Puzzles by Denis Berthier Pdf
"Pattern-Based Constraint Satisfaction and Logic Puzzles (Third Edition)" develops a pure logic, pattern-based perspective of solving the finite Constraint Satisfaction Problem (CSP), with emphasis on finding the "simplest" solution. Different ways of reasoning with the constraints are formalised by various families of "resolution rules", each of them carrying its own notion of simplicity. A large part of the book illustrates the power of the approach by applying it to various popular logic puzzles. It provides a unified view of how to model and solve them, even though they involve very different types of constraints: obvious symmetric ones in Sudoku, non-symmetric but transitive ones in Futoshiki, topological and geometric ones in Map colouring, Numbrix and Hidato, non-binary arithmetic ones in Kakuro and both non-binary and non-local ones in Slitherlink. It also shows that the most familiar techniques for these puzzles can be understood as mere application-specific presentations of the general rules. A free companion software (CSP-Rules-V2.1) implementing all the rules and above-mentioned applications is available on GitHub under the GPL license.
Pattern-Based Constraint Satisfaction and Logic Puzzles (Third Edition) by Denis Berthier Pdf
"Pattern-Based Constraint Satisfaction and Logic Puzzles (Third Edition)" develops a pure logic, pattern-based perspective of solving the finite Constraint Satisfaction Problem (CSP), with emphasis on finding the "simplest" solution. Different ways of reasoning with the constraints are formalised by various families of "resolution rules", each of them carrying its own notion of simplicity. A large part of the book illustrates the power of the approach by applying it to various popular logic puzzles. It provides a unified view of how to model and solve them, even though they involve very different types of constraints: obvious symmetric ones in Sudoku, non-symmetric but transitive ones in Futoshiki, topological and geometric ones in Map colouring, Numbrix and Hidato, non-binary arithmetic ones in Kakuro and both non-binary and non-local ones in Slitherlink. It also shows that the most familiar techniques for these puzzles can be understood as mere application-specific presentations of the general rules. A free companion software (CSP-Rules-V2.1) implementing all the rules and above-mentioned applications is available on GitHub under the GPL license.
User Manual and Research Notebooks for CSP-Rules by Denis Berthier Pdf
CSP-Rules is a generic pattern-based (or rule-based) solver of finite binary Constraint Satisfaction Problems (CSPs). This software is available on GitHub and it includes fully developed applications to various logic puzzles such as Sudoku, Latin Squares (allowing their Pandiagonal variant), Futoshiki, Kakuro, Numbrix, Hidato, Slitherlink and Map Colouring. CSP-Rules produces not only the solution to a CSP (as all the existing CSP solvers) but also a full "resolution path", i.e. a detailed justification for each step; this is a full mathematical proof of the solution. CSP-Rules and the present book are closely related to the author's book "Pattern Based Constraint Satisfaction and Logic Puzzles", where the fundamental theory underlying the approach is presented. This book includes an extended version of the original "Basic User Manual". But it also introduces new powerful generic rules (OR-chains) for taking advantage of almost-contradictory patterns. In particular, it applies these chains to the analysis of a newly discovered pattern (tridagon) and to the classification of a large database of extreme Sudoku puzzles that have it. It also adds the analyses of 630 impossible patterns and explains how to deal with such a large number of patterns. It shows that a handful of them provide almost the same resolution power as the full set. The long final two chapters are written as research notebooks on these very advanced topics.
What Is Constraint Satisfaction In artificial intelligence and operations research, the process of finding a solution through a set of constraints that impose conditions that the variables must satisfy is referred to as constraint satisfaction. Therefore, a solution is a collection of values for the variables that fulfills all of the constraints; more specifically, a solution is a point in the feasible region. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Constraint satisfaction Chapter 2: Boolean satisfiability problem Chapter 3: Search algorithm Chapter 4: Mathematical optimization Chapter 5: Constraint programming Chapter 6: Constraint satisfaction problem Chapter 7: Backtracking Chapter 8: 2-satisfiability Chapter 9: Nonlinear programming Chapter 10: WalkSAT (II) Answering the public top questions about constraint satisfaction. (III) Real world examples for the usage of constraint satisfaction in many fields. (IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of constraint satisfaction' technologies. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of constraint satisfaction.
Author : Dr. S. Murugan Publisher : SK Research Group of Companies Page : 215 pages File Size : 52,6 Mb Release : 2023-04-17 Category : Computers ISBN : 9789395341653
Artificial Intelligence with Machine Learning Concepts by Dr.M.Priya,Dr.R.Vijayashree,Mr.V.J.Rajakumar,Mr.S.S.Saravana Kumar Pdf
Dr.M.PRIYA, Assistant Professor, Department of Computer Technology and Data Science, Sri Krishna Arts and Science College, Coimbatore, Tamil Nadu, India. Dr.R.VIJAYASHREE, Assistant Professor, Department of Computer Technology and Data Science, Sri Krishna Arts and Science College, Coimbatore, Tamil Nadu, India. Mr.V.J.RAJAKUMAR, Assistant Professor, Department of Computer Technology and Data Science, Sri Krishna Arts & Science College, Coimbatore, Tamil Nadu, India. Mr.S.S.SARAVANA KUMAR, Research Scholar, Department of Computer Science, Sri Krishna Adithya College of Arts and Science, Coimbatore, Tamil Nadu, India.
Introduction of Artificial Intelligence by K.Gurnadha Gupta,C. Divya,Voruganti Ramesh,Tharini Benarji Pdf
Artificial intelligence Introduction(AI), the power of a computer or computer-controlled robot to perform tasks commonly related to intelligent beings. The term is usually applied to the project of developing systems endowed with the intellectual processes characteristic of humans. As well as, like the power to reason, discover meaning, generalize, or learn from experience. Since the event of the computer within the 1940s, it’s been demonstrated that computers are often programmed to hold out very complex tasks. For instance, discovering proofs for mathematical theorems or playing chess—with great proficiency. Still, despite continuing advances in computer processing speed and memory capacity, there are so far no programs. That will match human flexibility over wider domains or in tasks requiring much everyday knowledge. Moreover, some programs have attained the performance levels of human experts and professionals in performing certain specific tasks. So, Artificial intelligence introduction during this limited sense is found in applications as diverse as diagnosis, computer search engines. And also, voice or handwriting recognition to all but the only human behavior is ascribed to intelligence. While even the foremost complicated insect behavior isn’t taken as a sign of intelligence. What’s the difference? Consider the behavior of the sphecoid wasp, Sphex ichneumoneus. When the feminine wasp returns to her burrow with food, she first deposits it on the edge. Checks for intruders inside her burrow, and only then, if the coast is obvious, carries her food inside. The important nature of the wasp‘s instinctual behavior is revealed. If the food is moved a couple of inches faraway from the doorway to her burrow. Likewise, she is inside: on emerging, she is going to repeat the entire procedure as often because the food is displaced. Intelligence—conspicuously absent within the case of Sphex—must include the power to adapt to new circumstances. Psychologists generally don’t characterize human intelligence by only one trait but by the mixture of the many diverse abilities.
What Is Expert System In the field of artificial intelligence, an expert system is a type of computer program that simulates the abilities of a human expert to make judgment calls. Instead of using typical procedural code, expert systems reason through bodies of knowledge, which are primarily represented as if-then rules. This is in contrast to traditional computer programs, which tackle complicated issues by writing procedural code. In the 1970s, the first expert systems were developed, and later in the 1980s, their use became more widespread. Expert systems were one of the earliest forms of artificial intelligence (AI) software that was actually successful. An expert system can be broken down into its two component subsystems, which are the knowledge base and the inference engine. The knowledge base is a collection of facts and guidelines. The inference engine takes the rules and applies them to the known data in order to derive new information. The capabilities of explanation and debugging are also sometimes included in inference engines. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Expert system Chapter 2: Learning classifier system Chapter 3: AI winter Chapter 4: Constraint logic programming Chapter 5: Constraint satisfaction Chapter 6: CLIPS Chapter 7: Mycin Chapter 8: Knowledge engineering Chapter 9: Rule-based machine learning Chapter 10: CADUCEUS (expert system) (II) Answering the public top questions about expert system. (III) Real world examples for the usage of expert system in many fields. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of expert system. What Is Artificial Intelligence Series The Artificial Intelligence eBook series provides comprehensive coverage in over 200 topics. Each ebook covers a specific Artificial Intelligence topic in depth, written by experts in the field. The series aims to give readers a thorough understanding of the concepts, techniques, history and applications of artificial intelligence. Topics covered include machine learning, deep learning, neural networks, computer vision, natural language processing, robotics, ethics and more. The ebooks are written for professionals, students, and anyone interested in learning about the latest developments in this rapidly advancing field. The Artificial Intelligence eBook series provides an in-depth yet accessible exploration, from the fundamental concepts to the state-of-the-art research. With over 200 volumes, readers gain a thorough grounding in all aspects of Artificial Intelligence. The ebooks are designed to build knowledge systematically, with later volumes building on the foundations laid by earlier ones. This comprehensive series is an indispensable resource for anyone seeking to develop expertise in artificial intelligence.
Augmented User Manual for CSP-Rules-V2.1 by Denis Berthier Pdf
This book is the User Manual for CSP-Rules-V2.1, a generic pattern-based (or rule-based) solver of finite binary Constraint Satisfaction Problems (CSPs). The associated software, CSP-Rules-V2.1, is available on GitHub. It includes fully developed applications to logic puzzles such as Latin Squares, Sudoku, Futoshiki, Kakuro, Map Colouring, Numbrix, Hidato and Slithering. This third edition includes additions related to reducing the number of steps in a resolution path and to a newly discovered pattern (tridagon) for extremely hard puzzles.
Basic User Manual for CSP-Rules-V2.1 by Denis Berthier Pdf
This book is the User Manual for CSP-Rules-V2.1, a generic pattern-based (or rule-based) solver of finite binary Constraint Satisfaction Problems (CSPs). The associated software, CSP-Rules-V2.1, is available on GitHub. It includes fully developed applications to logic puzzles such as Latin Squares, Sudoku, Futoshiki, Kakuro, Map Colouring, Numbrix, Hidato and Slithering.
Basic User Manual for CSP-Rules-V2.1 (Second Edition) by Denis Berthier Pdf
This book is the User Manual for CSP-Rules-V2.1, a generic pattern-based (or rule-based) solver of finite binary Constraint Satisfaction Problems (CSPs). The associated software, CSP-Rules-V2.1, is available on GitHub. It includes fully developed applications to logic puzzles such as Latin Squares, Sudoku, Futoshiki, Kakuro, Map Colouring, Numbrix, Hidato and Slithering. This second edition includes additions related to reducing the number of steps in a resolution path.
The Art of Computer Programming, Volume 4B by Donald E. Knuth Pdf
The Art of Computer Programming is Knuth's multivolume analysis of algorithms. With the addition of this new volume, it continues to be the definitive description of classical computer science. Volume 4B, the sequel to Volume 4A, extends Knuth's exploration of combinatorial algorithms. These algorithms are of keen interest to software designers because ". . . a single good idea can save years or even centuries of computer time." The book begins with coverage of Backtrack Programming, together with a set of data structures whose links perform "delightful dances" and are ideally suited to this domain. New techniques for important applications such as optimum partitioning and layout are thereby developed. Knuth's writing is playful, and he includes dozens of puzzles to illustrate the algorithms and techniques, ranging from popular classics like edge-matching to more recent crazes like sudoku. Recreational mathematicians and computer scientists will not be disappointed! In the second half of the book, Knuth addresses Satisfiability, one of the most fundamental problems in all of computer science. Innovative techniques developed at the beginning of the twenty-first century have led to game-changing applications, for such things as optimum scheduling, circuit design, and hardware verification. Thanks to these tools, computers are able to solve practical problems involving millions of variables that only a few years ago were regarded as hopeless. The Mathematical Preliminaries Redux section of the book is a special treat, which presents basic techniques of probability theory that have become prominent since the original "preliminaries" were discussed in Volume 1. As in every volume of this remarkable series, the book includes hundreds of exercises that employ Knuth's ingenious rating system, making it easy for readers of varying degrees of mathematical training to find challenges suitable to them. Detailed answers are provided to facilitate self-study. "Professor Donald E. Knuth has always loved to solve problems. In Volume 4B he now promotes two brand new and practical general problem solvers, namely (0) the Dancing Links Backtracking and (1) the SAT Solver. To use them, a problem is defined declaratively (0) as a set of options, or (1) in Boolean formulae. Today's laptop computers, heavily armoured with very high speed processors and ultra large amounts of memory, are able to run either solver for problems having big input data. Each section of Volume 4B contains a multitudinous number of tough exercises which help make understanding surer. Happy reading!" --Eiiti Wada, an elder computer scientist, UTokyo "Donald Knuth may very well be a great master of the analysis of algorithms, but more than that, he is an incredible and tireless storyteller who always strikes the perfect balance between theory, practice, and fun. [Volume 4B, Combinatorial Algorithms, Part 2] dives deep into the fascinating exploration of search spaces (which is quite like looking for a needle in a haystack or, even harder, to prove the absence of a needle in a haystack), where actions performed while moving forward must be meticulously undone when backtracking. It introduces us to the beauty of dancing links for removing and restoring the cells of a matrix in a dance which is both simple to implement and very efficient." --Christine Solnon, Department of Computer Science, INSA Lyon Register your book for convenient access to downloads, updates, and/or corrections as they become available.
The "Hidden Logic of Sudoku" provides the first systematic perspective of the logical symmetries of the popular game. These are fully exploited to define new graphical representations, new kinds of resolution rules and a precedence ordering of the rules consistent with their logical complexity. The set of rules defined in the book is illustrated with a hundred of puzzles together with their full resolution paths. It suffices to solve almost any puzzle without making guesses or assuming the uniqueness of a solution. It has been fed into an Artificial Intelligence (AI) engine and a large database of puzzles has been processed, leading to a precise evaluation of the efficiency of each rule. The book is intended for both advanced Sudoku players (who will discover many new facets of the game and a new, systematic approach to the resolution rules) and for teachers or students of Logic or AI (who will appreciate the strict logical foundations).
Foundations of Constraint Satisfaction by Edward Tsang Pdf
Foundations of Constraint Satisfaction discusses the foundations of constraint satisfaction and presents algorithms for solving constraint satisfaction problems (CSPs). Most of the algorithms described in this book are explained in pseudo code, and sometimes illustrated with Prolog codes (to illustrate how the algorithms could be implemented). Comprised of 10 chapters, this volume begins by defining the standard CSP and the important concepts around it and presenting examples and applications of CSPs. The reader is then introduced to the main features of CSPs and CSP solving techniques (problem reduction, searching, and solution synthesis); some of the most important concepts related to CSP solving; and problem reduction algorithms. Subsequent chapters deal with basic control strategies of searching which are relevant to CSP solving; the significance of ordering the variables, values and compatibility checking in searching; specialized search techniques which gain their efficiency by exploiting problem-specific features; and stochastic search approaches (including hill climbing and connectionist approaches) for CSP solving. The book also considers how solutions can be synthesized rather than searched for before concluding with an analysis of optimization in CSPs. This monograph can be used as a reference by artificial intelligence (AI) researchers or as a textbook by students on advanced AI courses, and should also help knowledge engineers apply existing techniques to solve CSPs or problems which embed CSPs.
Constraint Satisfaction in Logic Programming by Pascal Van Hentenryck Pdf
This book tackles classic problems from operations research and circuit design using a logic programming language embedding consistency techniques, a paradigm emerging from artificial intelligence research. Van Hentenryck proposes a new approach to solving discrete combinatorial problems using these techniques.Logic programming serves as a convenient language for stating combinatorial problems, but its "generate and test" paradigm leads to inefficient programs. Van Hentenryck's approach preserves one of the most useful features of logic programming - the duality of its semantics - yet allows a short development time for the programs while preserving most of the efficiency of special purpose programs written in a procedural language.Embedding consistency techniques in logic programming allows for ease and flexibility of programming and short development time because constraint propagation and tree-search programming are abstracted away from the user. It also enables logic programs to be executed efficiently as consistency techniques permit an active use of constraints to remove combinations of values that cannot appear in a solution Van Hentenryck presents a comprehensive overview of this new approach from its theoretical foundations to its design and implementation, including applications to real life combinatorial problems.The ideas introduced in "Constraint Satisfaction in Logic Programming "have been used successfully to solve more than a dozen practical problems in operations research and circuit design, including disjunctive scheduling, warehouse location, cutting stock car sequencing, and microcode labeling problems.Pascal Van Hentenryck is a member of the research staff at the European Computer Industry Research Centre. "Constraint Satisfaction in Logic Programming" is based on research for the Centre's CHIP project. As an outgrowth of this project, a new language (CHIP) that will include consistency techniques has been developed for commercial use. The book is included in the Logic Programming series edited by Ehud Shapiro.
