Flexible Interpretations: A Computational Model for Dynamic Uncertainty Assessment
This work addresses uncertainty assessment for interpretation tasks in real domains, but it appears incremental as it builds on existing concepts without specifying novel breakthroughs.
The paper tackles the problem of dynamic uncertainty assessment during interpretation tasks in real domains, focusing on developing a computational model that supports multiple interpretations and smooth transitions in real time, with each step involving input interpretation and confidence re-establishment, but no concrete results or numbers are provided.
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).