Flexible Interpretations: A Computational Model for Dynamic Uncertainty Assessment

TL;DR

This paper presents a computational model for dynamic uncertainty assessment that supports multiple interpretations and smooth transitions in real-time interpretation tasks, focusing on control structures that adapt as new inputs are processed.

Contribution

It introduces a novel control structure for computational interpretation models enabling real-time management of multiple interpretations and confidence updates.

Findings

Supports multiple interpretations simultaneously

Enables smooth transitions between interpretations

Provides real-time confidence re-establishment

Abstract

The investigations reported in this paper center on the process of dynamic uncertainty assessment during interpretation tasks in real domain. In particular, we are interested here in the nature of the control structure of computer programs that can support multiple interpretation and smooth transitions between them, in real time. Each step of the processing involves the interpretation of one input item and the appropriate re-establishment of the system's confidence of the correctness of its interpretation(s).