Incremental Recompilation of Knowledge
G. Gogic, C. H. Papadimitriou, M. Sideri

TL;DR
This paper introduces an incremental recompilation method that efficiently updates Horn formula approximations, overcoming static limitations and complexity issues of previous knowledge compilation schemes.
Contribution
It proposes a novel inductive scheme combining Horn approximation with model-based updates for efficient knowledge base revision.
Findings
The scheme is inductive and maintains positive properties after updates.
Horn envelopes and cores are efficiently computable after minimum-change updates.
The approach is free of the complexity issues faced by previous static schemes.
Abstract
Approximating a general formula from above and below by Horn formulas (its Horn envelope and Horn core, respectively) was proposed by Selman and Kautz (1991, 1996) as a form of ``knowledge compilation,'' supporting rapid approximate reasoning; on the negative side, this scheme is static in that it supports no updates, and has certain complexity drawbacks pointed out by Kavvadias, Papadimitriou and Sideri (1993). On the other hand, the many frameworks and schemes proposed in the literature for theory update and revision are plagued by serious complexity-theoretic impediments, even in the Horn case, as was pointed out by Eiter and Gottlob (1992), and is further demonstrated in the present paper. More fundamentally, these schemes are not inductive, in that they may lose in a single update any positive properties of the represented sets of formulas (small size, Horn structure, etc.). In…
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