Artificial Intelligence - Special issue on knowledge representation
Semiring-based constraint satisfaction and optimization
Journal of the ACM (JACM)
Backtracking algorithms for disjunctions of temporal constraints
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Chaff: engineering an efficient SAT solver
Proceedings of the 38th annual Design Automation Conference
SAT-Based Procedures for Temporal Reasoning
ECP '99 Proceedings of the 5th European Conference on Planning: Recent Advances in AI Planning
Constraint Processing
Efficient solution techniques for disjunctive temporal reasoning problems
Artificial Intelligence
Semirings for Soft Constraint Solving and Programming (LECTURE NOTES IN COMPUTER SCIENCE)
Semirings for Soft Constraint Solving and Programming (LECTURE NOTES IN COMPUTER SCIENCE)
Algorithms for constraint-based temporal reasoning with preferences
Algorithms for constraint-based temporal reasoning with preferences
Handbook of Constraint Programming (Foundations of Artificial Intelligence)
Handbook of Constraint Programming (Foundations of Artificial Intelligence)
A logical approach to efficient Max-SAT solving
Artificial Intelligence
Complexity of terminating preference elicitation
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Low-cost addition of preferences to DTPs and TCSPs
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Temporal preference optimization as weighted constraint satisfaction
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Any time, complete algorithm for finding utilitarian optimal solutions to STPPs
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
Uncertainty in preference elicitation and aggregation
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Incompleteness and incomparability in preference aggregation
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Valued constraint satisfaction problems: hard and easy problems
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Tractable Pareto optimization of temporal preferences
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Temporal constraint reasoning with preferences
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Dealing with incomplete preferences in soft constraint problems
CP'07 Proceedings of the 13th international conference on Principles and practice of constraint programming
SMT-COMP: satisfiability modulo theories competition
CAV'05 Proceedings of the 17th international conference on Computer Aided Verification
Solving disjunctive temporal problems with preferences using maximum satisfiability
AI Communications - 18th RCRA International Workshop on “Experimental evaluation of algorithms for solving problems with combinatorial explosion”
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In this paper, we consider both the modelling and optimization of preferences in problems of constraint-based temporal reasoning. The Disjunctive Temporal Problems with Preferences (DTPP) - a formulation that combines the rich expressive power of the Disjunctive Temporal Problem with the introduction of metric preference functions - is studied, and transformed into a corresponding constraint system that we name the Valued DTP (VDTP). We show that for a broad family of optimization criteria, the VDTP can express the same solution space as the DTPP, under the assumption of arbitrary piecewise-constant preference functions. We then generalize the powerful search strategies from decision-based DTP literature to accomplish the efficient optimization of temporal preferences. In contrast to the previous state-of-the-art system (which addresses the optimization of temporal preferences using a SAT formulation), we instead employ a meta-CSP search space that has traditionally been used to solve DTPs without preferences. Our approach supports a variety of objective functions (such as utilitarian optimality or maximin optimality) and can accommodate any compliant valuation structure. We also demonstrate that key pruning techniques commonly used for temporal satisfiability (particularly, the removal of subsumed variables and semantic branching) are naturally suited to prevent the exploration of redundant search nodes during optimization that may otherwise be encountered when resolving a typical VDTP derived from a DTPP. Finally, we present empirical results showing that an implementation of our approach consistently outperforms prior algorithms by orders of magnitude.