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Approximation Fixpoint Theory with Refined Approximation Spaces

Published: June 19, 2025 | arXiv ID: 2506.16294v1

By: Linde Vanbesien, Bart Bogaerts, Marc Denecker

Potential Business Impact:

Makes computer thinking more flexible and powerful.

Business Areas:
Natural Language Processing Artificial Intelligence, Data and Analytics, Software

Approximation Fixpoint Theory (AFT) is a powerful theory covering various semantics of non-monotonic reasoning formalisms in knowledge representation such as Logic Programming and Answer Set Programming. Many semantics of such non-monotonic formalisms can be characterized as suitable fixpoints of a non-monotonic operator on a suitable lattice. Instead of working on the original lattice, AFT operates on intervals in such lattice to approximate or construct the fixpoints of interest. While AFT has been applied successfully across a broad range of non-monotonic reasoning formalisms, it is confronted by its limitations in other, relatively simple, examples. In this paper, we overcome those limitations by extending consistent AFT to deal with approximations that are more refined than intervals. Therefore, we introduce a more general notion of approximation spaces, showcase the improved expressiveness and investigate relations between different approximation spaces.

Country of Origin
🇧🇪 Belgium

Page Count
10 pages

Category
Computer Science:
Artificial Intelligence