Situation Recognition and Hypothesis Management Using Petri Nets
2009 (English)In: Modeling Decisions for Artificial Intelligence: Proceedings of the 6th International Conference (MDAI 2009) / [ed] Vicenç Torra, Yasuo Narukawa, Masahiro Inuiguchi, Springer Berlin/Heidelberg, 2009, p. 303-314Conference paper, Published paper (Refereed)
Abstract [en]
Situation recognition – the task of tracking states and identifying situations - is a problem that is important to look into for aiding decision makers in achieving enhanced situation awareness. The purpose of situation recognition is, in contrast to producing more data and information, to aid decision makers in focusing on information that is important for them, i.e. to detect potentially interesting situations. In this paper we explore the applicability of a Petri net based approach for modeling and recognizing situations, as well as for managing the hypothesis space coupled to matching situation templates with the present stream of data.
Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2009. p. 303-314
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 5861 LNAI
Keywords [en]
Situation recognition, information fusion, petri nets, hypothesis management, multi-agent activity recognition, situation assessment
National Category
Computer Sciences
Research subject
Technology
Identifiers
URN: urn:nbn:se:his:diva-3536DOI: 10.1007/978-3-642-04820-3_28ISI: 000276970400028Scopus ID: 2-s2.0-84886491111ISBN: 978-3-642-04819-7 ISBN: 978-3-642-04820-3 OAI: oai:DiVA.org:his-3536DiVA, id: diva2:284173
Conference
Modeling Decisions for Artificial Intelligence : 6th International Conference, MDAI 2009, Awaji Island, Japan, November 30–December 2, 2009
2010-01-042010-01-042018-01-12Bibliographically approved