Solving conditional and composite constraint satisfaction problems
Proceedings of the 2007 ACM symposium on Applied computing
IEEE Intelligent Systems
A constraint-based product configurator for mass customisation
International Journal of Computer Applications in Technology
Managing Conditional and Composite CSPs
CAI '07 Proceedings of the 20th conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence
IEA/AIE '08 Proceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence
Search heuristics for constraint-aided embodiment design
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Extending dynamic backtracking to solve weighted conditional CSPs
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Conditional constraint satisfaction: logical foundations and complexity
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
CP'07 Proceedings of the 13th international conference on Principles and practice of constraint programming
Constraint patterns and search procedures for CP-based random test generation
HVC'07 Proceedings of the 3rd international Haifa verification conference on Hardware and software: verification and testing
High-level modeling of component-based CSPs
SBIA'10 Proceedings of the 20th Brazilian conference on Advances in artificial intelligence
Conditional and composite temporal CSPs
Applied Intelligence
Querying e-catalogs using content summaries
ODBASE'06/OTM'06 Proceedings of the 2006 Confederated international conference on On the Move to Meaningful Internet Systems: CoopIS, DOA, GADA, and ODBASE - Volume Part I
Engineering Applications of Artificial Intelligence
Reasoning about conditional constraint specification problems and feature models
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
Freedom through constraints: User-oriented architectural design
Advanced Engineering Informatics
Beyond physical product configuration --Configuration in unusual domains
AI Communications - Intelligent Engineering Techniques for Knowledge Bases
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Constraints are a powerful general paradigm for representing knowledge in intelligent systems. The standard constraint satisfaction paradigm involves variables over a discrete value domain and constraints which restrict the solutions to allowed value combinations. This standard paradigm is inapplicable to problems which are either:(a) mixed, involving both numeric and discrete variables, or(b) conditional,1 containing variables whose existence depends on the values chosen for other variables, or(c) both, conditional and mixed.We present a general formalism which handles both exceptions in an integral search framework. We solve conditional problems by analyzing dependencies between constraints that enable us to directly compute all possible configurations of the CSP rather than discovering them during search. For mixed problems, we present an enumeration scheme that integrates numeric variables with discrete ones in a single search process. Both techniques take advantage of enhanced propagation rule for numeric variables that results in tighter labelings than the algorithms commonly used. From real world examples in configuration and design, we identify several types of mixed constraints, i.e. constraints defined over numeric and discrete variables, and propose new propagation rules in order to take advantage of these constraints during problem solving.