Foundations of a functional approach to knowledge representation.
Artificial Intelligence
ModGen: theorem proving by model generation
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Problem solving by searching for models with a theorem prover
Artificial Intelligence
Limited reasoning in first-order knowledge bases
Artificial Intelligence
Tractable reasoning via approximation
Artificial Intelligence
On the complexity of bounded-variable queries (extended abstract)
PODS '95 Proceedings of the fourteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Limited reasoning in first-order knowledge bases with full introspection
Artificial Intelligence
Anytime approximate model reasoning
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
A non-deterministic semantics for tractable inference
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Proceedings of the seventh ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Symbolic Logic and Mechanical Theorem Proving
Symbolic Logic and Mechanical Theorem Proving
Annals of Mathematics and Artificial Intelligence
CLIN-S - A Semantically Guided First-Order Theorem Prover
Journal of Automated Reasoning
Implementing the Davis–Putnam Method
Journal of Automated Reasoning
A Logic for Anytime Deduction and Anytime Compilation
JELIA '98 Proceedings of the European Workshop on Logics 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
Efficient first-order semantic deduction techniques
Efficient first-order semantic deduction techniques
SCOTT: a model-guided theorem prover
IJCAI'93 Proceedings of the 13th international joint conference on Artifical intelligence - Volume 1
SEM: a system for enumerating models
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Pushing the envelope: planning, propositional logic, and stochastic search
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Approximate Inference In Default Logic And Circumscription
Fundamenta Informaticae
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In classical approaches to knowledge representation, reasoners are assumed to derive all the logical consequences of their knowledge base. As a result, reasoning in the first-order case is only semi-decidable. Even in the restricted case of finite universes of discourse, reasoning remains inherently intractable, as the reasoner has to deal with two independent sources of complexity: unbounded chaining and unbounded quantification. The purpose of this study is to handle these difficulties in a logic-oriented framework based on the paradigm of approximate reasoning. The logic is semantically founded on the notion of resource, an accuracy measure, which controls at the same time the two barriers of complexity. Moreover, a stepwise technique is included for improving approximations. Finally, both sound approximations and complete ones are covered. Based on the logic, we develop an approximation algorithm with a simple modification of classical instance-based theorem provers. The procedure yields approximate proofs whose precision increases as the reasoner has more resources at her disposal. The algorithm is interruptible, improvable, dual, and can be exploited for anytime computation. Moreover, the algorithm is flexible enough to be used with a wide range of propositional satisfiability methods.