Exact and approximate reasoning about temporal relations
Computational Intelligence
Artificial Intelligence - Special issue on knowledge representation
Reasoning about qualitative temporal information
Artificial Intelligence - Special volume on constraint-based reasoning
Complexity and algorithms for reasoning about time: a graph-theoretic approach
Journal of the ACM (JACM)
Reasoning about temporal relations: a maximal tractable subclass of Allen's interval algebra
Journal of the ACM (JACM)
Combining qualitative and quantitative constraints in temporal reasoning
Artificial Intelligence
MAAI '96 Proceedings of symposia in applied mathematics on Mathematical aspects of artificial intelligence
Maintaining knowledge about temporal intervals
Communications of the ACM
Algorithmic Graph Theory and Perfect Graphs (Annals of Discrete Mathematics, Vol 57)
Algorithmic Graph Theory and Perfect Graphs (Annals of Discrete Mathematics, Vol 57)
Graph Theory, Combinatorics and Algorithms: Interdisciplinary Applications (Operations Research/Computer Science Interfaces Series)
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Reasoning about time is a very ancient discipline, perhaps as old as prehistoric man. These ancient humans had discovered how long to roast their hunted meat and how to dry and age the skins of animals. They learned how and when to plant seeds, and were guided by the cycles of the sun, moon and the seasons. Our ancestors knew that day followed night and night followed day, and they had some notion of duration of day and night. This basic temporal knowledge was exploited to develop a sense of planning, taking advantage of observation and experience. For example, they would have observed that deer drink at the river at a certain time of the day, or that .sh are easier to catch in the early morning. Early humans could recognize the changing seasons, and adapted their behavior in order to expect and avoid some of the dangers of cold and hunger by preparing in advance.