A Reason Maintenace System Dealing with Vague Data

TL;DR

This paper presents a reason maintenance system that integrates fuzzy logic into an ATMS to handle incomplete and vague data, enabling nonmonotonic reasoning and dynamic revision of conclusions.

Contribution

It introduces a novel extension of an ATMS with fuzzy logic to manage uncertainty and vagueness in reasoning processes.

Findings

Supports nonmonotonic inference with vague data

Enables revision of conclusions upon contradictions

Handles incomplete information effectively

Abstract

A reason maintenance system which extends an ATMS through Mukaidono's fuzzy logic is described. It supports a problem solver in situations affected by incomplete information and vague data, by allowing nonmonotonic inferences and the revision of previous conclusions when contradictions are detected.