Many fundamental combinatorial problems, arising in such diverse fields as artificial intelligence, logic, graph theory, and linear algebra, can be formulated as Boolean constraint satisfaction problems (CSP). This book is devoted to the study of the complexity of such problems. The authors' goal is to develop a framework for classifying the complexity of Boolean CSP in a uniform way. In doing so, they bring out common themes underlying many concepts and results in both algorithms and complexity theory. The results and techniques presented here show that Boolean CSP provide an excellent framework for discovering and formally validating "global" inferences about the nature of computation.

Presents a novel form of a compendium that classifies an infinite number of problems by using a rule-based approach.

Nowadays constraint satisfaction problems (CSPs) are ubiquitous in many different areas of computer science, from artificial intelligence and database systems to circuit design, network optimization, and theory of programming languages. Consequently, it is important to analyze and pinpoint the computational complexity of certain algorithmic tasks related to constraint satisfaction. The complexity-theoretic results of these tasks may have a direct impact on, for instance, the design and processing of database query languages, or strategies in data-mining, or the design and implementation of planners. This state-of-the-art survey contains the papers that were invited by the organizers after conclusion of an International Dagstuhl-Seminar on Complexity of Constraints, held in Dagstuhl Castle, Germany, in October 2006. A number of speakers were solicited to write surveys presenting the state of the art in their area of expertise. These contributions were peer-reviewed by experts in the field and revised before they were collated to the 9 papers of this volume. In addition, the volume contains a reprint of a survey by Kolaitis and Vardi on the logical approach to constraint satisfaction that first appeared in 'Finite Model Theory and its Applications', published by Springer in 2007.

The topic of this book is the following optimisation problem: given a set of discrete variables and a set of functions, each depending on a subset of the variables, minimise the sum of the functions over all variables. This fundamental research problem has been studied within several different contexts of discrete mathematics, computer science and artificial intelligence under different names: Min-Sum problems, MAP inference in Markov random fields (MRFs) and conditional random fields (CRFs), Gibbs energy minimisation, valued constraint satisfaction problems (VCSPs), and, for two-state variables, pseudo-Boolean optimisation. In this book the author presents general techniques for analysing the structure of such functions and the computational complexity of the minimisation problem, and he gives a comprehensive list of tractable cases. Moreover, he demonstrates that the so-called algebraic approach to VCSPs can be used not only for the search for tractable VCSPs, but also for other questions such as finding the boundaries to the applicability of certain algorithmic techniques. The book is suitable for researchers interested in methods and results from the area of constraint programming and discrete optimisation.

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 volume contains the papers presented at the 30th Symposium on Mathematical Foundations of Computer Science (MFCS 2005) held in Gdansk, Poland from August 29th to September 2nd, 2005.

This volume constitutes the proceedings of the 2nd International Joint C- ference on Automated Reasoning (IJCAR 2004) held July 4–8, 2004 in Cork, Ireland. IJCAR 2004 continued the tradition established at the ?rst IJCAR in Siena,Italyin2001,whichbroughttogetherdi?erentresearchcommunitieswo- ing in automated reasoning. The current IJCAR is the fusion of the following conferences: CADE: The International Conference on Automated Deduction, CALCULEMUS: Symposium on the Integration of Symbolic Computation and Mechanized Reasoning, FroCoS: Workshop on Frontiers of Combining Systems, FTP: The International Workshop on First-Order Theorem Proving, and TABLEAUX: The International Conference on Automated Reasoning with Analytic Tableaux and Related Methods. There were 74 research papers submitted to IJCAR as well as 12 system descriptions. After extensive reviewing, 26 research papers and 6 system - scriptions were accepted for presentation at the conference and publication in this volume. In addition, this volume also contains papers from the three invited speakers and a description of the CADE ATP system competition. We would like to acknowledge the enormous amount of work put in by the members of the program committee, the various organizing and steering c- mittees, the IJCAR o?cials, the invited speakers, and the additional referees named on the following pages. We would also like to thank Achim Brucker and Barbara Geiser for their help in producing this volume.

Annotation This book constitutes the refereed proceedings of the 21st International Symposium on Algorithms and Computation, ISAAC 2010, held in Jeju, South Korea in December 2010.The 77 revised full papers presented were carefully reviewed and selected from 182 submissions for inclusion in the book. This volume contains topics such as approximation algorithm; complexity; data structure and algorithm; combinatorial optimization; graph algorithm; computational geometry; graph coloring; fixed parameter tractability; optimization; online algorithm; and scheduling.

This book constitutes the thoroughly refereed post workshop proceedings of the 8th International Workshop on Approximation and Online Algorithms, WAOA 2010, held in Liverpool, UK, in September 2010 as part of the ALGO 2010 conference event. The 23 revised full papers presented were carefully reviewed and selected from 58 submissions. The workshop covered areas such as algorithmic game theory, approximation classes, coloring and partitioning, competitive analysis, computational finance, cuts and connectivity, geometric problems, inapproximability results, echanism design, network design, packing and covering, paradigms for design and analysis of approximation and online algorithms, parameterized complexity, randomization techniques, real-world applications, and scheduling problems.