Abstract
Solving challenging computational problems involving time has been a critical component in the development of artificial intelligence systems almost since the inception of the field. .is book provides a concise introduction to the core computational elements of temporal reasoning for use in AI systems for planning and scheduling, as well as systems that extract temporal information from data. It presents a survey of temporal frameworks based on constraints, both qualitative and quantitative, as well as of major temporal consistency techniques. .e book also introduces the reader to more recent extensions to the core model that allow AI systems to explicitly represent temporal preferences and temporal uncertainty. .is book is intended for students and researchers interested in constraint-based temporal reasoning. It provides a self-contained guide to the different representations of time, as well as examples of recent applications of time in AI systems. © 2014 by Morgan and Claypool.
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Barták, R., Morris, R. A., & Venable, K. B. (2014). An introduction to constraint-based temporal reasoning. Synthesis Lectures on Artificial Intelligence and Machine Learning, 26, 1–123. https://doi.org/10.2200/S00557ED1V01Y201312AIM026
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