Abstract
Describes an extension to deKleer's (1986) assumption-based truth maintenance system (ATMS) that shows promise in making large-scale problem solving more tractable. The approach assumes a problem can be decomposed into a hierarchically related set of subproblems, each of which is represented within its own ATMS partition. It is shown how this decomposition can be used to circumvent the exponential growth in the size of node labels which often occurs in attempting to apply the ATMS. The authors present some experimental results showing efficiency gains, and discuss the impact of partitioning on label consistency, soundness, minimality, and completeness. >
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