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
Algorithms for Distributed Constraint Satisfaction: A Review
Autonomous Agents and Multi-Agent Systems
Distributing the control of a temporal network among multiple agents
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Random constraint satisfaction: Easy generation of hard (satisfiable) instances
Artificial Intelligence
Managing complex scheduling problems with dynamic and hybrid constraints
Managing complex scheduling problems with dynamic and hybrid constraints
Augmenting disjunctive temporal problems with finite-domain constraints
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 3
Hybrid constraint tightening for solving hybrid scheduling problems
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
TACAS'08/ETAPS'08 Proceedings of the Theory and practice of software, 14th international conference on Tools and algorithms for the construction and analysis of systems
Conditional and composite temporal CSPs
Applied Intelligence
Solving the multiagent selection and scheduling problem
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Using hybrid scheduling for the semi-autonomous formation of expert teams
Future Generation Computer Systems
Distributed reasoning for multiagent simple temporal problems
Journal of Artificial Intelligence Research
Group planning with time constraints
Annals of Mathematics and Artificial Intelligence
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Hybrid Scheduling Problems (HSPs) combine temporal and finite-domain variables via hybrid constraints that dictate that specific bounds on temporal constraints rely on assignments to finite-domain variables. Hybrid constraint tightening (HCT) reformulates hybrid constraints to apply the tightest consistent temporal bound possible, assisting in search space pruning. The contribution of this paper is to empirically evaluate the HCT approach using a state-of-the-art Satisfiability Modulo Theory solver on realistic, interesting problems related to developing scheduling agents to assist people with cognitive impairments. We demonstrate that HCT leads to orders of magnitude reduction of search complexity. The success of HCT is enhanced as we apply HCT to hybrid constraints involving increasing numbers of finite-domain variables and finite-domains with increasing size, as well as hybrid constraints expressing increasing temporal precision. We show that while HCT reduces search complexity for all but the simplest problems, the relative effectiveness is dampened on problems with partially conditional temporal constraints and hybrid constraints with increasing temporal disjunctions. Finally, we present our preliminary investigations that indicate that HCT can assist in increasing communication efficacy in a multiagent setting.