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"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…mehr

Produktbeschreibung
"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.
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Autorenporträt
Denis Berthier graduated from Ecole Polytechnique (X68, Paris, France) and was full Professor of Logic, Artificial Intelligence and Epistemology of Information Technologies at Institut Mines Télécom, France. He is the author of a series of books on Pattern-Based Constraint Satisfaction.