The event calculus in probabilistic logic programming with annotated disjunctions

McAreavey, Kevin; Bauters, Kim; Liu, Weiru; Hong, Jun

Abstract

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.

• Presentation Conference Type: Conference Paper (unpublished)
• Conference Name: AAMAS 2017 - the 16th International Conference on Autonomous Agents and Multiagent Systems
• Start Date: May 8, 2017
• End Date: May 12, 2017
• Acceptance Date: May 8, 2017
• Publication Date: May 8, 2017
• Deposit Date: Apr 25, 2017
• Peer Reviewed: Peer Reviewed
• Pages: 105-113
• Keywords: the event calculus, event reasoning, probabilistic logic programming,; ProbLog, annotated disjunction
• Public URL: https://uwe-repository.worktribe.com/output/887908
• Publisher URL: http://www.ifaamas.org/Proceedings/aamas2017/pdfs/p105.pdf
• Additional Information: Title of Conference or Conference Proceedings : AAMAS 2017: The 16th International Conference on Autonomous Agents and Multiagent Systems
• Contract Date: May 21, 2018