Linear Temporal Public Announcement Logic: a new perspective for reasoning about the knowledge of multi-classifiers

TL;DR

This paper introduces LTPAL, a formal model combining PAL and LTL to analyze knowledge in classification processes, including data streams and video object detection, offering a new perspective on reasoning about classifiers.

Contribution

The paper proposes LTPAL, a novel formal transition system integrating PAL and LTL for reasoning about classifier knowledge in various data contexts.

Findings

LTPAL effectively models knowledge in classification processes.

Application to video-stream object detection demonstrates practical utility.

Formalization captures natural language properties in classification reasoning.

Abstract

In this note, a formal transition system model called LTPAL to extract knowledge in a classification process is suggested. The model combines the Public Announcement Logic (PAL) and the Linear Temporal Logic (LTL). In the model, first, we consider classifiers, which capture single-framed data. Next, we took classifiers for data-stream data input into consideration. Finally, we formalize natural language properties in LTPAL with a video-stream object detection sample.