Temporal representation and reasoning in artificial intelligence: A review

The explicit representation and reasoning about time is an important problem in many areas of artificial intelligence. Over the last 10–15 years, it has been attracting the attention of many researchers. Several temporal reasoning systems, differing in design issues related to ontology of time, underlying temporal logic, temporal constraints used and algorithms employed, have been developed. In this survey, important representational issues which determine a temporal reasoning system are introduced. In particular, several important notions like change, causality, actions are described in terms of time. For each issue different choices available in the literature are discussed. The most influential approaches to temporal reasoning in artificial intelligence are analyzed in terms of these major representational issues.