Decidability and expressiveness aspects of logic queries
PODS '87 Proceedings of the sixth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Foundations of deductive databases and logic programming
Finding optimal derivation in redundant knowledge bases
Artificial Intelligence
Constraints and redundancy in datalog
PODS '92 Proceedings of the eleventh ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
PODS '92 Proceedings of the eleventh ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Equivalence, query-reachability and satisfiability in Datalog extensions
PODS '93 Proceedings of the twelfth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Irrelevance reasoning in knowledge-based systems
Irrelevance reasoning in knowledge-based systems
Independence of logic database queries and update
PODS '90 Proceedings of the ninth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Equivalences Among Relational Expressions with the Union and Difference Operators
Journal of the ACM (JACM)
The compleat guide to MRS
A theory of justified reformulations
A theory of justified reformulations
Controlling communication in distributed planning using irrelevance reasoning
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
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Identifying that parts of a knowledge base (KB) are irrelevant to a specific query is a powerful method of controlling search during problem solving. However, finding methods of such irrelevance reasoning and analyzing their utility are open problems. We present a framework based on a proof-theoretic analysis of irrelevance that enables us to address these problems. Within the framework, we focus on a class of strong-irrelevance claims and show that they have several desirable properties. For example, in the context of Horn-rule theories, we show that strong-irrelevance claims can be derived efficiently either by examining the KB or as logical consequences of other strong-irrelevance claims. An important aspect is that our algorithms reason about irrelevance using only a small part of the KB. Consequently, the reasoning is efficient and the derived irrelevance claims are independent of changes to other parts of the KB.