This book provides a significant step towards bridging the areas of Boolean satisfiability and constraint satisfaction by answering the question why SAT-solvers are efficient on certain classes of CSP instances which are hard to solve for standard constraint solvers. The author also gives theoretical reasons for choosing a particular SAT encoding for several important classes of CSP instances. Boolean satisfiability and constraint satisfaction emerged independently as new fields of computer science, and different solving techniques have become standard for problem solving in the two areas. Even though any propositional formula (SAT) can be viewed as an instance of the general constraint satisfaction problem (CSP), the implications of this connection have only been studied in the last few years. The book will be useful for researchers and graduate students in artificial intelligence and theoretical computer science.

This book provides a significant step towards bridging the areas of Boolean satisfiability and constraint satisfaction by answering the question why SAT-solvers are efficient on certain classes of CSP instances which are hard to solve for standard constraint solvers. The author also gives theoretical reasons for choosing a particular SAT encoding for several important classes of CSP instances. Boolean satisfiability and constraint satisfaction emerged independently as new fields of computer science, and different solving techniques have become standard for problem solving in the two areas. Even though any propositional formula (SAT) can be viewed as an instance of the general constraint satisfaction problem (CSP), the implications of this connection have only been studied in the last few years. The book will be useful for researchers and graduate students in artificial intelligence and theoretical computer science.

This book constitutes the proceedings of the 26th International Conference on Principles and Practice of Constraint Programming, CP 2020, held in Louvain-la-Neuve, Belgium, in September 2020. The conference was held virtually due to the COVID-19 pandemic. The 55 full papers presented in this volume were carefully reviewed and selected from 122 submissions. They deal with all aspects of computing with constraints including theory, algorithms, environments, languages, models, systems, and applications such as decision making, resource allocation, scheduling, configuration, and planning. The papers were organized according to the following topics/tracks: technical track; application track; and CP and data science and machine learning.

This book constitutes the refereed proceedings of the 21st International Conference on Theory and Applications of Satisfiability Testing, SAT 2018, held in Oxford, UK, in July 2018. The 20 revised full papers, 4 short papers, and 2 tool papers were carefully reviewed and selected from 58 submissions. The papers address different aspects of SAT interpreted in a broad sense, including theoretical advances (such as exact algorithms, proof complexity, and other complexity issues), practical search algorithms, knowledge compilation, implementation-level details of SAT solvers and SAT-based systems, problem encodings and reformulations, applications as well as case studies and reports on findings based on rigorous experimentation. They are organized in the following topical sections: maximum satisfiability; conflict driven clause learning; model counting; quantified Boolean formulae; theory; minimally unsatisfiable sets; satisfiability modulo theories; and tools and applications.

This book constitutes the refereed conference proceedings of the 20th International Conference on Principles and Practice of Constraint Programming, CP 2014, held in Lyon, France, in September 2014. The 65 revised papers presented together with 4 invited talks were carefully selected from 108 submissions. The scope of CP 2014 includes all aspects of computing with constraints, including theory, algorithms, environments, languages, models, systems, and applications such as decision making, resource allocation, and agreement technologies.

This book presents 8 papers accompanying the lectures of leading researchers given at the 6th edition of the International School on Formal Methods for the Design of Computer, Communication and Software Systems (SFM 2006). SFM 2006 was devoted to formal techniques for hardware verification and covers several aspects of the hardware design process, including hardware design languages and simulation, property specification formalisms, automatic test pattern generation, symbolic trajectory evaluation, and more.

Algorithms are essential building blocks of computer applications. However, advancements in computer hardware, which render traditional computer models more and more unrealistic, and an ever increasing demand for efficient solution to actual real world problems have led to a rising gap between classical algorithm theory and algorithmics in practice. The emerging discipline of Algorithm Engineering aims at bridging this gap. Driven by concrete applications, Algorithm Engineering complements theory by the benefits of experimentation and puts equal emphasis on all aspects arising during a cyclic solution process ranging from realistic modeling, design, analysis, robust and efficient implementations to careful experiments. This tutorial - outcome of a GI-Dagstuhl Seminar held in Dagstuhl Castle in September 2006 - covers the essential aspects of this process in ten chapters on basic ideas, modeling and design issues, analysis of algorithms, realistic computer models, implementation aspects and algorithmic software libraries, selected case studies, as well as challenges in Algorithm Engineering. Both researchers and practitioners in the field will find it useful as a state-of-the-art survey.