Changing times: a causal theory of probabilistic temporal reasoning
Ahmed Y. Tawfik, Eric M. Neufeld · Journal of Experimental & Theoretical Artificial Intelligence · 1999
A framework for representing and reasoning about uncertain temporal information is presented. This framework relies on a non-recursive representation of probabilities as functions of time. The representation is compatible with survival analysis techniques, and allows the use of regressive survival models to represent common interaction patterns. In another departure from previous temporal probabilistic knowledge representations, surprise measures are used to detect and correct poor probability estimates. The present framework relies mainly on a theory of causality, while still allowing the representation of phenomena without requiring a complete understanding of causes.