A sufficient condition for backtrack-bounded search
Journal of the ACM (JACM)
Artificial Intelligence
Network-based heuristics for constraint-satisfaction problems
Artificial Intelligence
Knowledge Structuring and Constraint Satisfaction: The Mapsee Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
An incremental constraint solver
Communications of the ACM
A Sufficient Condition for Backtrack-Free Search
Journal of the ACM (JACM)
A new method for solving constraint satisfaction problems
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 1
Towards a generic model of configuraton tasks
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 2
Optimizing customer's selection for configurable product in B2C e-commerce application
Computers in Industry
Conditional constraint satisfaction: logical foundations and complexity
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
A weighted CSP approach to cost-optimal planning
AI Communications
Conflict-directed relaxation of constraints in content-based recommender systems
IEA/AIE'06 Proceedings of the 19th international conference on Advances in Applied Artificial Intelligence: industrial, Engineering and Other Applications of Applied Intelligent Systems
Conditional and composite temporal CSPs
Applied Intelligence
Integrating CSP decomposition techniques and BDDs for compiling configuration problems
CPAIOR'05 Proceedings of the Second international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
An intuitive tool for constraint based grammars
CSLP'04 Proceedings of the First international conference on Constraint Solving and Language Processing
A constraint satisfaction approach to resolving product configuration conflicts
Advanced Engineering Informatics
An automated approach to generating efficient constraint solvers
Proceedings of the 34th International Conference on Software Engineering
Constraint-Based refactoring with foresight
ECOOP'12 Proceedings of the 26th European conference on Object-Oriented Programming
Managing dynamic CSPs with preferences
Applied Intelligence
Engineering Applications of Artificial Intelligence
Reasoning about conditional constraint specification problems and feature models
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Personalized diagnoses for inconsistent user requirements
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Adaptive attribute selection for configurator design via shapley value
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
A novel approach for dynamic authorisation planning in constrained workflow systems
Proceedings of the 6th International Conference on Security of Information and Networks
Maintaining alternative values in constraint-based configuration
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Beyond physical product configuration --Configuration in unusual domains
AI Communications - Intelligent Engineering Techniques for Knowledge Bases
WeCoTin --A practical logic-based sales configurator
AI Communications - Intelligent Engineering Techniques for Knowledge Bases
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Constraint satisfaction (CSP) is a powerful and extensively used framework for describing search problems. A CSP is typically defined as the problem of finding consistent assignment of values to a fixed set of variables given some constraints over these variables. However, for many synthesis tasks such as configuration and model composition, the set of variables that are relevant to a solution and must be assigned values changes dynamically in response to decisions made during the course of problem solving. In this paper, we formalize this notion as a dynamic constraint satisfaction problem that uses two types of constraints. Compatibility constraints correspond to those traditionally found in CSPs, namely, constraints over the values of variables. Activity constraints describe conditions under which a variable may or may not be actively considered as a part of a final solution. We present a language for expressing four types of activity constraints in terms of variable values and variables being considered. We then describe an implemented algorithm that enables tight interaction between constraints about variable activity and constraints about variable values. The utility of this approach is demonstrated for configuration and model composition tasks.