Abstract
We introduce a modular framework for formalizing reasoning with incomplete and inconsistent information. This framework is composed of non-deterministic semantic structures and distance-based considerations. The combination of these two principles leads to a variety of entailment relations that can be used for reasoning about non-deterministic phenomena and are inconsistency-tolerant. We investigate the basic properties of these entailments and demonstrate their usefulness in the context of model-based diagnostic systems.
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Arieli, O., Zamansky, A. (2009). Non-deterministic Distance Semantics for Handling Incomplete and Inconsistent Data. In: Sossai, C., Chemello, G. (eds) Symbolic and Quantitative Approaches to Reasoning with Uncertainty. ECSQARU 2009. Lecture Notes in Computer Science(), vol 5590. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02906-6_68
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DOI: https://doi.org/10.1007/978-3-642-02906-6_68
Publisher Name: Springer, Berlin, Heidelberg
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