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Temporal representation and reasoning in artificial intelligence: Issues and approaches

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Abstract

Time is one of the most relevant topics in AI. It plays a major role in several areas, ranging from logical foundations to applications of knowledge‐based systems. In this paper, we survey a wide range of research in temporal representation and reasoning, without committing ourselves to the point of view of any specific application. The organization of the paper follows the commonly recognized division of the field in two main subfields: reasoning about actions and change, and reasoning about temporal constraints. We give an overview of the basic issues, approaches, and results in these two areas, and outline relevant recent developments. Furthermore, we briefly analyze the major emerging trends in temporal representation and reasoning as well as the relationships with other well‐established areas, such as temporal databases and logic programming.

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Chittaro, L., Montanari, A. Temporal representation and reasoning in artificial intelligence: Issues and approaches. Annals of Mathematics and Artificial Intelligence 28, 47–106 (2000). https://doi.org/10.1023/A:1018900105153

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