Temporal Reasoning with Constraints on Fluents and Events

Planning and Scheduling

Volume

Proceedings of the AAAI Conference on Artificial Intelligence, 12

Planning: Representation

We propose a propositional language for temporal reasoning that is computationally effective yet expressive enough to describe information about fluents, events and temporal constraints. Although the complete inference algorithm is exponential, we characterize a tractable core with limited expressibility and inferential power. Our results render a variety of constraint propagation techniques applicable for reasoning with constraints on Auents.