Abstract
We are concerned with formal models of reasoning under uncertainty. Many approaches to this problem are known in the literature e.g. Dempster-Shafer theory [29], [42], bayesian-based reasoning [21], [29], belief networks [29], many-valued logics and fuzzy logics [6], non-monotonic logics [29], neural network logics [14]. We propose rough mereology developed by the last two authors [22-25] as a foundation for approximate reasoning about complex objects. Our notion of a complex object includes, among others, proofs understood as schemes constructed in order to support within our knowledge assertions/hypotheses about reality described by our knowledge incompletely.
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Komorowski, J., Polkowski, L.T. & Skowron, A. Towards a Rough Mereology-Based Logic for Approximate Solution Synthesis. Part 1. Studia Logica 58, 143–184 (1997). https://doi.org/10.1023/A:1004900200790
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DOI: https://doi.org/10.1023/A:1004900200790