Constrained decision revision
Charles J. Petrie · National Conference on Artificial Intelligence · 1992
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.