Weighted Conditional EL{^}bot Knowledge Bases with Integer Weights: an ASP Approach
Laura Giordano (DISIT, Universit\`a del Piemonte Orientale, Italy),, Daniele Theseider Dupr\'e (DISIT, Universit\`a del Piemonte Orientale, Italy)

TL;DR
This paper introduces an ASP-based approach for reasoning with weighted conditional EL^bot knowledge bases using integer weights, enhancing the logical semantics of multilayer perceptrons.
Contribution
It presents a novel encoding of concept-wise multipreference entailment for weighted KBs with integer weights using ASP and asprin.
Findings
Effective encoding of weighted KBs with ASP
Enhanced reasoning capabilities for concept-wise multipreference
Potential applications in neural-symbolic integration
Abstract
Weighted knowledge bases for description logics with typicality have been recently considered under a "concept-wise" multipreference semantics (in both the two-valued and fuzzy case), as the basis of a logical semantics of Multilayer Perceptrons. In this paper we consider weighted conditional EL^bot knowledge bases in the two-valued case, and exploit ASP and asprin for encoding concept-wise multipreference entailment for weighted KBs with integer weights.
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