Foundations of a functional approach to knowledge representation.
Artificial Intelligence
Approximate inference in default logic and circumscription
ECAI '92 Proceedings of the 10th European conference on Artificial intelligence
Tractable reasoning via approximation
Artificial Intelligence
Knowledge compilation and theory approximation
Journal of the ACM (JACM)
Generating hard satisfiability problems
Artificial Intelligence - Special volume on frontiers in problem solving: phase transitions and complexity
Tractable Reasoning in Artificial Intelligence
Tractable Reasoning in Artificial Intelligence
Approximate Reasoning about Combined Knowledge
ATAL '97 Proceedings of the 4th International Workshop on Intelligent Agents IV, Agent Theories, Architectures, and Languages
A new algorithm for incremental prime implicate generation
IJCAI'93 Proceedings of the 13th international joint conference on Artifical intelligence - Volume 1
Knowledge compilation using theory prime implicates
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Compilation for critically constrained knowledge bases
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
On Anytime Coherence-Based Reasoning
ECSQARU '01 Proceedings of the 6th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
A Logic for Approximate First-Order Reasoning
CSL '01 Proceedings of the 15th International Workshop on Computer Science Logic
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One of the main characteristics of reasoning in knowledge based systems is its high computational complexity. Anytime deduction and anytime compilation are two attractive approaches that have been proposed for addressing such a difficulty. The first one offers a compromise between the time complexity needed to compute approximate answers and the quality of these answers. The second one proposes a trade-off between the space complexity of the compiled theory and the number of possible answers it can efficiently process. The purpose of our study is to define a logic which handles these two approaches by incorporating several major features. First, the logic is semantically founded on the notion of resource which captures both the accuracy and the cost of approximation. Second, a stepwise procedure is included for improving approximate answers. Third, both sound approximations and complete ones are covered. Fourth and finally, the reasoning task may be done off-line and compiled theories can be used for answering many queries.