Actions and Events in Interval Temporal Logic

  • James F. Allen
  • George Ferguson


Representing and reasoning about the dynamic aspects of the world — primarily about actions and events — is a problem of interest to many different disciplines. In Artificial Intelligence (AI), we are interested in such problems for a number of reasons — in particular, to model the reasoning of intelligent agents as they plan to act in the world and to reason about causal effects in the world. More specifically, a general representation of actions and events has to support the following somewhat overlapping tasks:
  • Prediction: Given a description of a scenario, including actions and events, what will (or is most likely to) happen?

  • Planning: Given an initial description of the world and a desired goal, find a course of action that will (or is most likely to) achieve that goal.

  • Explanation: Given a set of observations about the world, find the best explanation of the data. When the observations are another agent’s actions and the explanation desired is the agent’s plan, the problem is called plan recognition.


Temporal Logic External Event Simultaneous Action Reasoning Task Axiom Schema 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media Dordrecht 1997

Authors and Affiliations

  • James F. Allen
  • George Ferguson

There are no affiliations available

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