Minimizing conflicts: a heuristic repair method for constraint satisfaction and scheduling problems
Artificial Intelligence - Special volume on constraint-based reasoning
Solution reuse in dynamic constraint satisfaction problems
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Fast planning through planning graph analysis
Artificial Intelligence
New methods to color the vertices of a graph
Communications of the ACM
Solution Techniques for Constraint Satisfaction Problems: Advanced Approaches
Artificial Intelligence Review
Dynamic Flexible Constraint Satisfaction
Applied Intelligence
Reduction operations in fuzzy or valued constraint satisfaction
Fuzzy Sets and Systems - Optimisation and decision
The Knowledge Engineering Review
Hard, flexible and dynamic constraint satisfaction
The Knowledge Engineering Review
Valued constraint satisfaction problems: hard and easy problems
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Total-order multi-agent task-network planning for contract bridge
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Flexible planning using fuzzy description logics: Theory and application
Applied Soft Computing
Fuzzy Sets and Rough Sets for Scenario Modelling and Analysis
RSFDGrC '09 Proceedings of the 12th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
Risk assessment of serious crime with fuzzy random theory
Information Sciences: an International Journal
Backward-Chaining flexible planning
ICMLC'05 Proceedings of the 4th international conference on Advances in Machine Learning and Cybernetics
Flexible goal recognition via graph construction and analysis
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part II
Finding rough and fuzzy-rough set reducts with SAT
Information Sciences: an International Journal
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Constraint satisfaction is a fundamental Artificial Intelligence technique for knowledge representation and inference. However, the formulation of a static constraint satisfaction problem (CSP) with hard, imperative constraints is insufficient to model many real problems. Fuzzy constraint satisfaction provides a more graded viewpoint. Priorities and preferences are placed on individual constraints and aggregated via fuzzy conjunction to obtain a satisfaction degree for a solution to the problem. This paper examines methods for solving an important instance of dynamic flexible constraint satisfaction (DFCSP) combining fuzzy CSP and restriction/relaxation based dynamic CSP: fuzzy rrDFCSP. This allows the modelling of complex situations where both the set of constraints may change over time and there is flexibility inherent in the definition of the problem. This paper also presents a means by which classical planning can be extended via fuzzy sets to enable flexible goals and preferences to be placed on the use of planning operators. A range of plans can be produced, trading compromises made versus the length of the plan. The flexible planning operators are close in definition to fuzzy constraints. Hence, through a hierarchical decomposition of the planning graph, the work shows how flexible planning reduces to the solution of a set of fuzzy rrDFCSPs.