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Concurrent Constraint Programming introduces a new and rich class of programming languages based on the notion of computing with partial information, or constraints, that synthesize and extend work on concurrent logic programming and that offer a promising approach for treating thorny issues in the semantics of concurrent, nondeterministic programming languages. Saraswat develops an elegant and semantically tractable framework for computing with constraints, emphasizing their importance for communication and control in concurrent, programming languages. He describes the basic paradigm, illustrates its structure, discusses various augmentations, gives a simple implementation of a concrete language, and specifies its connections with other formalisms. In this framework, concurrently executing agents communicate by placing and checking constraints on shared variables in a common store. The major form of concurrency control in the system is through the operations of Atomic Tell -- an agent may instantaneously place constraints only if they are consistent with constraints that have already been placed -- and Blocking Ask -- an agent must block when it checks a constraint that is not yet known to hold. Other operations at a finer granularity of atomicity are also presented. Saraswat introduces and develops the concurrent constraint family of programming languages based on these ideas, shows how various constraint systems can naturally realize data structures common in computer science, and presents a formal operational semantics for many languages in the concurrent constraint family. In addition, he provides a concrete realization of the paradigm on a sequential machine by presenting a compiler for the concurrent constraint language Herbrand and demonstrates a number of constraint-based concurrent programming techniques that lead to novel presentations of algorithms for many concurrent programming problems.
Constraint programming aims at supporting a wide range of complex applications, which are often modeled naturally in terms of constraints. Early work, in the 1960s and 1970s, made use of constraints in computer graphics, user interfaces, and artificial intelligence. Such work introduced a declarative component in otherwise-procedural systems to reduce the development effort.
Programming languages are often classified according to their paradigms, e.g. imperative, functional, logic, constraint-based, object-oriented, or aspect-oriented. A paradigm characterizes the style, concepts, and methods of the language for describing situations and processes and for solving problems, and each paradigm serves best for programming in particular application areas. Real-world problems, however, are often best implemented by a combination of concepts from different paradigms, because they comprise aspects from several realms, and this combination is more comfortably realized using multiparadigm programming languages. This book deals with the theory and practice of multiparadigm constraint programming languages. The author first elaborates on programming paradigms and languages, constraints, and the merging of programming concepts which yields multiparadigm (constraint) programming languages. In the second part the author inspects two concrete approaches on multiparadigm constraint programming – the concurrent constraint functional language CCFL, which combines the functional and the constraint-based paradigms and allows the description of concurrent processes; and a general framework for multiparadigm constraint programming and its implementation, Meta-S. The book is appropriate for researchers and graduate students in the areas of programming and artificial intelligence.
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
Concurrent constraint programming (ccp) is a recent development in programming language design. Its central contribution is the notion of partial information provided by a shared constraint store. This constraint store serves as a communication medium between concurrent threads of control and as a vehicle for their synchronization. Objects for Concurrent Constraint Programming analyzes the possibility of supporting object-oriented programming in ccp. Starting from established approaches, the book covers various object models and discusses their properties. Small Oz, a sublanguage of the ccp language Oz, is used as a model language for this analysis. This book presents a general-purpose object system for Small Oz and describes its implementation and expressivity for concurrent computation. Objects for Concurrent Constraint Programming is written for programming language researchers with an interest in programming language aspects of concurrency, object-oriented programming, or constraint programming. Programming language implementors will benefit from the rigorous treatment of the efficient implementation of Small Oz. Oz programmers will get a first-hand view of the design decisions that lie behind the Oz object system.
The definitive reference on Constraint Handling Rules, from the creator of the language.
Constraints; Simplification, optimization and implication; Finite constraint domains; Constraint logic programming; Simple modeling; Using data structures; Controlling search; Modelling with finite domain constraints; Advanced programming techniques; CLP systems; Other constraint programming languages; Constraint databases; Index.
Constraint programming (CP) is a declarative programming paradigm with many academic and industrial applications (from n-queens to planning, vehicle routing, and optimization, among other fields). Music composition has been one of these applications since the earliest works on automatic harmonization, and it remains a very special and challenging one due to its artistic (and highly subjective) nature. The early works on CP in music were limited to classical music composition, as the harmonization and counterpoint rules naturally translate into constraints. However, when contemporary composers began to be interested in constraints, CP became an essential tool in computer-assisted composition systems. As several contemporary musical pieces have now been composed "with constraints", it is reasonable to ask why CP applies so naturally to music, and what the particular features of musical problems are. This book presents information about recently developed musical CP systems from both the scientist's and composer's point-of-view. It will therefore be of interest to students and researchers of music technology, composers in the computer music scene, and music software companies-especially those trying to model high level musical behaviors (i.e., intelligent arpeggiation/arrangement on synthesizers, "Band in a Box" software, etc.), perform music data mining, and execute music taste engineering for online music delivery.
Teaching the science and the technology of programming as a unified discipline that shows the deep relationships between programming paradigms. This innovative text presents computer programming as a unified discipline in a way that is both practical and scientifically sound. The book focuses on techniques of lasting value and explains them precisely in terms of a simple abstract machine. The book presents all major programming paradigms in a uniform framework that shows their deep relationships and how and where to use them together. After an introduction to programming concepts, the book presents both well-known and lesser-known computation models ("programming paradigms"). Each model has its own set of techniques and each is included on the basis of its usefulness in practice. The general models include declarative programming, declarative concurrency, message-passing concurrency, explicit state, object-oriented programming, shared-state concurrency, and relational programming. Specialized models include graphical user interface programming, distributed programming, and constraint programming. Each model is based on its kernel language—a simple core language that consists of a small number of programmer-significant elements. The kernel languages are introduced progressively, adding concepts one by one, thus showing the deep relationships between different models. The kernel languages are defined precisely in terms of a simple abstract machine. Because a wide variety of languages and programming paradigms can be modeled by a small set of closely related kernel languages, this approach allows programmer and student to grasp the underlying unity of programming. The book has many program fragments and exercises, all of which can be run on the Mozart Programming System, an Open Source software package that features an interactive incremental development environment.
Constraint programming is like an octopus spreading its tentacles into databases, operations research, artificial intelligence, and many other areas. The concept of constraint programming was introduced in artificial intelligence and graphics in the 1960s and 1970s. Now the related techniques are used and studied in many fields of computing. Different aspects of constraint processing are investigated in theoretical computer science, logic programming, knowledge representation, operations research, and related application domains. Constraint programming has been included in the lists of related topics of many conferences. Nevertheless, only in 1993 were the first forums held, devoted as a whole to this field of knowledge. These were the First Workshop on Principles and Practice of Constraint Programming (PPCP'93) which was held in Newport, Rhode Island, USA, April 28-30, the International Workshop on Constraint Processing (at CSAM'93) held in St. Petersburg, Russia, July 20-21, and the NATO Advanced Study Institute (NATO AS!) on Constraint Programming held in Parnu, Estonia, August 13-24. NATO A Sis are aimed to be schools bringing together leading researchers and practitioners from industry and academia in some area of knowledge to provide a concise picture of the work done and results obtained by different groups. This is intended for dissemination of advanced knowledge not yet taught regularly in of new topics university. However, ASis must also encourage the introduction into university curricula as well as foster international scientific contacts.