Evolving Petri Nets for Situation Recognition
2010 (English) In: GEM 2010: Proceedings of the 2010 International Conference on Genetic and Evolutionary Methods / [ed] Hamid R. Arabnia, Ray R. Hashemi, Ashu M. G. Solo, CSREA Press, 2010, p. 29-35Conference paper, Published paper (Refereed)
Abstract [en]
Situation recognition is an important problem to address for developing newcapabilities in the surveillance domain. It is concerned with recognizing a priori defined situations of interest, which can be of concurrent and temporal nature, possibly occurring in a continuous flow of data and information. It is however a complex task to manually define what constitutes an interesting situation, and we therefore investigate the possibility of using genetic algorithms for evolving Petri nets for situation recognition. Our results show that: (1) it is possible to evolve complex Petri nets, (2) it is possible to increase the performance of manually designed Petri nets, and (3) a dynamic genome representation consisting of complex genes is beneficial compared to a representation consisting of bit strings.
Place, publisher, year, edition, pages CSREA Press, 2010. p. 29-35
Keywords [en]
Evolving structure, genetic algorithms, genome representation, petri nets, situation recognition
National Category
Computer and Information Sciences
Research subject Technology
Identifiers URN: urn:nbn:se:his:diva-4642 ISBN: 1-60132-145-7 OAI: oai:DiVA.org:his-4642 DiVA, id: diva2:392189
Conference 2010 International Conference on Genetic and Evolutionary Methods, GEM 2010, July 12-15, 2010, Las Vegas Nevada, USA
2011-01-262011-01-262018-01-12 Bibliographically approved