The Event Calculus in Probabilistic Logic Programs with Annotated Disjunctions

Kevin McAreavey, Kim Bauters, Weiru Liu, Jun Hong

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

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We propose a new probabilistic extension to the event calculus using the probabilistic logic programming (PLP) language ProbLog, and a language construct called the annotated disjunction. This is the first extension of the event calculus capable of handling numerous sources of uncertainty (e.g. from primitive event observations and from composite event definitions). It is also the first extension capable of handling multiple sources of event observations (e.g. in multi-sensor environments). We describe characteristics of this new extension (e.g. rationality of conclusions), and prove some important properties (e.g. validity in ProbLog). Our extension is directly implementable in ProbLog, and we successfully apply it to the problem of activity recognition under uncertainty in an event detection data set obtained from vision analytics of bus surveillance video.
Original languageEnglish
Title of host publicationProceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS2017)
Subtitle of host publicationMay 8–12, 2017, São Paulo, Brazil
PublisherInternational Foundation for Autonomous Agents and MultiAgent Systems
Number of pages9
Publication statusPublished - May 2017


  • The event calculus
  • event reasoning
  • probabilistic logic programming
  • ProbLog
  • annotated disjunction


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