On the Non-Monotonic Behavior of the Event Calculus for Deriving Maximal Time Intervals

making previous intervals no longer derivable. As a consequence, a meaningful ordering over partially specified event orderings may not be based on inclusion of the corresponding Computed Intervals sets. A monotonic version of the calculus is then proposed and compared to the original. We discuss why it is not immediately viable for AI applications, and show how it can be used to order partially specified orderings. A valuation function is defined that chooses among alternative orderings the one(s) which minimizes the separation from the result obtainable by the monotonic version.

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