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• [P1097] A Framework for Reasoning Under Uncertainty with Temporal Constraints
  Author(s): Eugene Santos, Deqing Li, John Thomas Wilkinson
  
  

  Abstract
  Time is the key stimuli to change, causality and interaction which are the main components of a dynamic world. Therefore, the modeling of knowledge, especially in complex and dynamic domains like economics, sociology, and ecology, must incorporate the concept of time. Although there has been much research over the years on the representation of knowledge (causality, implication, and uncertainty) and on the representation of time, it has been a continuing challenge to unify these in a meaningful and useful fashion. In this paper, we propose a framework for reasoning under uncertainty with temporal constraints. The framework is extended from Bayesian knowledge-bases (BKBs), which represent uncertainty using an "if-then" structure and probability theory. By adding temporal constraints to BKBs, the framework provides a comprehensive model that incorporates the semantics of both time and uncertainty.

  
   

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