A qualitative physics based on confluences
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Artificial Intelligence
Readings in nonmonotonic reasoning
Readings in nonmonotonic reasoning
Symbolic Logic and Mechanical Theorem Proving
Symbolic Logic and Mechanical Theorem Proving
An Incremental Method for Generating Prime Implicants/Implicates
An Incremental Method for Generating Prime Implicants/Implicates
A comparison of ATMS and CSP techniques
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 1
Scaling up logic-based truth maintenance systems via fact garbage collection
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Non-Clausal Reasoning with Definite Theories
Fundamenta Informaticae
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This paper presents a new approach for exploiting Truth Maintenance Systems(TMSs) which makes them simpler to use without necessarily incurring a substantial performance penalty. The basic intuition behind this approach is to convey the locality of the knowledge representation of the problem solver to the TMS. The TMS then uses this locality information to control and restrict its inferences. The new TMSs accept arbitrary propositional formulae as input and use general Boolean Constraint Propagation(BCP) to answer queries about whether a particular literal follows from the formulae. Our TMS exploits the observation that if the set of propositional formulae are converted to their prime implicates, then BCP is both efficient and logically complete. This observation allows the problem solver to influence the degree of completeness of the TMS by controlling how many implicates are constructed. This control is exerted by using the locality in the original task to guide which combinations of formulae should be reduced to their prime implicates. This approach has been implemented and tested both within Assumption-Based Truth Maintenance Systems and Logic-Based Truth Maintenance Systems.