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A Unified View on Forgetting and Strong Equivalence Notions in Answer Set Programming

AAAI 2024 · Continual learning › Online and replay-based · approach: Dynamic expansion and isolation · 1 citations (OpenAlex)

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Introduces relativized strong A-simplification (a relaxation of strong simplification where context programs range over a set B), gives necessary and sufficient conditions and an operator combining projection with relativized strong persistence forgetting, plus complexity results for ASP.

Problem

Strong persistence forgetting, faithful abstraction and strong simplification in answer set programming have related characterizations via strong equivalence, but it was unclear how these notions unify; existing simplification notions require context programs over the full vocabulary.

Approach

Relativizes strong simplification by restricting the context programs to a vocabulary B, defining B-SE-models and A-B-SE-models, and deriving a criterion Omega_{A,B} so that strong equivalence, relativized strong equivalence, faithful abstraction, strong simplification and strong persistence all become special cases.

Key results

Surprising findings

Limitations

Experimental setup

Builds on: strong persistence forgetting strong simplification (Saribatur and Woltran) relativized strong equivalence (Woltran 2004) faithful omission abstraction (Zhang/Zhou) SP-forgetting criterion Omega (Goncalves et al.)

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