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Constraint satisfaction and constraint programming have shown to be very simple but powerful ideas, with applications in various areas. Still, in the last ten years, the simple notion of constraints has shown some deficiencies concerning both theory and practice, typically in the way over-constrained problems and preferences are treated. For this reason, the notion of soft constraints has been introduced with semiring-based soft constraints and valued constraints being the two main general frameworks. This book includes formal definitions and properties of semiring-based soft constraints, as well as their use within constraint logic programming and concurrent constraint programming. Moreover, the author shows how to adapt existing notions and techniques such as abstraction and interchangeability to the soft constraint framework and it is demonstrated how soft constraints can be used in some application areas, such as security. Overall, this book is a great starting point for anyone interested in understanding the basics of semiring-based soft constraints.
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
This book constitutes the refereed proceedings of the 13th International Conference on Principles and Practice of Constraint Programming, CP 2007. It contains 51 revised full papers and 14 revised short papers presented together with eight application papers and the abstracts of two invited lectures. All current issues of computing with constraints are addressed, ranging from methodological and foundational aspects to solving real-world problems in various application fields.
This book constitutes the refereed proceedings of the 8th International Conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems, CPAIOR 2011, held in Berlin, Germany, in May 2011. The 13 revised full papers and 7 revised short papers presented together with 3 invited lectures were carefully reviewed and selected from 35 submissions. The papers are focused on both theoretical and practical, application-oriented issues and present current research with a special focus on the integration and hybridization of the approaches of constraint programming, artificial intelligence, and operations research technologies for solving large scale and complex real life combinatorial optimization problems.
Presented are the theory and applications of soft computing paradigms including knowledge-based techniques, neural networks, fuzzy systems and genetic algorithms in engineering system design. The book contains 11 chapters. The first four provide an introduction to to the knowledge-based systems, neural networks, fuzzy systems and evolutionary computing techniques. The last 7 chapters include the applications of knowledge-based systems in engineering: productivity, quality and technology transfer; knowledge-based sytems in real-time applications; logic grammer in electronic circuit representation; applications of neural networks; evolution of neural structure based on cellular automata; application of ART and ARTMAP in self-organising learning, recognition and production; and applications of fuzzy systems.
Most real-life problems involve making decisions to optimally achieve a number of criteria while satisfying some hard or soft constraints. In this book several methods for solving such problems are presented by the leading experts in the area. The book also contains a number of very interesting application papers which demonstrate theoretical modelling, analysing and solution of real-life problems.
Brings together chapters by experts involved in a new area based on the confluence of genetic algorithms, fuzzy systems, and neural networks. Papers cover the broad ground of fuzzy logic control, neural fuzzy systems, genetic fuzzy systems, process control, and adaptive systems. Topics include the composition of heterogeneous control laws, ellipsoidal learning and fuzzy throttle control for platoons of smart cars, supervised and unsupervised learning, and propagation and satisfaction of flexible constraints. Annotation copyright by Book News, Inc., Portland, OR
For over a decade, a large number of governments have embarked on economic reforms to strengthen the competitiveness of their countries in the world market and improve the standards of living of their populations. By far the most extensive reforms, both in depth and scope, have occurred since the late 1980s in the former communist economies of Central and Eastern Europe and East Asia. Despite vast differences in initial conditions and reform design, Martin Raiser argues that a central ingredient of the success of these reforms must be the hardening of the budget constraint for domestic producers. To verify this hypothesis, Raiser develops an analytical framework that links the concept of the soft budget constraint to issues of economic reform in developing countries, and examines indicators of the degree of budget softness with particular emphasis on the institutional deficiencies that may undermine the credibility of macroeconomic stabilization and the effectiveness of price signals. In his empirical analysis, Raiser relates the indicators of budget softness to the inflation and growth records of thirty-one developing countries. The cases of Poland and China further illuminate his theory by pointing toward the institutional arrangements that may hinder the effective hardening of budget constraints in transition economies. Finally, Raiser analyzes enterprise level data for China to verify the link between budget softness and technical and allocative inefficiency. Soft Budget Constraints will be of notable interest to those scholars and students of economics specializing in development and transition economics.