Principles and Practice of Constraint Programming
This book constitutes the refereed conference proceedings of the 23nd International Conference on Principles and Practice of Constraint Programming, CP 2017, held in Melbourne, Australia from August 28, 2017 until September 1, 2017. The conference is colocated with the 20th International Conference on Theory and Applications of Satisfiability Testing (SAT 2017) and the 33rd International Conference on Logic Programming. The 46 revised full papers presented were carefully reviewed and selected from 115 submissions. The scope of the contributions includes all aspects of computing with constraints, including theory, algorithms, environments, languages, models, systems, and applications such as decision making, resource al location, scheduling, configuration, and planning. The papers are grouped into the following tracks: technical track; application track; machine learning & CP track; operations research & CP track; satisfiability & CP track, test and verification & CP track; journal & sister conference track.
Principles and Practice of Constraint Programming
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.
Principles and Practice of Constraint Programming
This book constitutes the proceedings of the 24th International Conference on Principles and Practice of Constraint Programming, CP 2018, held in Lille, France, in August 2018.The 41 full and 9 short papers presented in this volume were carefully reviewed and selected from 114 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: main technical track; applications track; CP and data science; CP and music; CP and operations research; CP, optimization and power system management; multiagent and parallel CP; and testing and verification.
Principles of Constraint Programming
Constraints are everywhere: most computational problems can be described in terms of restrictions imposed on the set of possible solutions, and constraint programming is a problem-solving technique that works by incorporating those restrictions in a programming environment. It draws on methods from combinatorial optimisation and artificial intelligence, and has been successfully applied in a number of fields from scheduling, computational biology, finance, electrical engineering and operations research through to numerical analysis. This textbook for upper-division students provides a thorough and structured account of the main aspects of constraint programming. The author provides many worked examples that illustrate the usefulness and versatility of this approach to programming, as well as many exercises throughout the book that illustrate techniques, test skills and extend the text. Pointers to current research, extensive historical and bibliographic notes, and a comprehensive list of references will also be valuable to professionals in computer science and artificial intelligence.
Principles and Practice of Constraint Programming
This book constitutes the proceedings of the 25th International Conference on Principles and Practice of Constraint Programming, CP 2019, held in Stamford, CT, USA, France, in September/October 2019. The 44 full papers presented in this volume were carefully reviewed and selected from 118 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; multi-agent and parallel CP track; testing and verification track; CP and data science track; computational sustainability; and CP and life sciences track.
