Constrained Decision Revision

Natural Language

Volume

Proceedings of the AAAI Conference on Artificial Intelligence, 10

Planning

This paper synthesizes general constraint satisfaction and classical AI planning into a theory of incremental change that accounts for multiple objectives and contingencies. The hypothesis is that this is a new and useful paradigm for problem solving and re-solving. A truth maintenance-based architecture derived from the theory is useful for contingent assignment problems such as logistics planning.