Possibilistic decreasing persistence

TL;DR

This paper introduces a possibilistic approach to model decreasing persistence in temporal data, allowing for more nuanced reasoning about the likelihood of fluents over time, and compares it with probabilistic methods.

Contribution

It presents a formal possibilistic framework for decreasing persistence, integrating nonmonotonic reasoning with possibility theory, and offers a comparison with existing probabilistic approaches.

Findings

Formal model of decreasing persistence using possibility theory

Demonstration of nonmonotonic inference based on decreasing persistence

Comparison showing advantages over probabilistic projection methods

Abstract

A key issue in the handling of temporal data is the treatment of persistence; in most approaches it consists in inferring defeasible confusions by extrapolating from the actual knowledge of the history of the world; we propose here a gradual modelling of persistence, following the idea that persistence is decreasing (the further we are from the last time point where a fluent is known to be true, the less certainly true the fluent is); it is based on possibility theory, which has strong relations with other well-known ordering-based approaches to nonmonotonic reasoning. We compare our approach with Dean and Kanazawa's probabilistic projection. We give a formal modelling of the decreasing persistence problem. Lastly, we show how to infer nonmonotonic conclusions using the principle of decreasing persistence.