Evolving Petri Net Situation Templates for Situation Recognition

• Situation recognition is an important problem to address in order to enhance the capabilities of modern surveillance systems. Situation recognition is concerned with finding a priori defined situations that possibly are instantiated in the present flow of information. It can be a rather tricky task to manually define templates for situations that evolve over time, and to at the same time achieve good results with respect to recall and precision on a situation recognition task. In this paper we present some initial results concerning the task of applying genetic algorithms to evolve Petri net based situation templates of interesting situations. Our results show that it is possible to evolve Petri nets that are on par with manually defined templates. However, more research is needed in order to establish the actual effects it has on recall and precision. 

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap -- Systemvetenskap, informationssystem och informatik (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Information Systems (hsv//eng)

Nyckelord

Genetic algorithms

petri nets

situation assessment

situation recognition

Computer and systems science

Data- och systemvetenskap

Technology

Teknik

Skövde Artificial Intelligence Lab (SAIL)

Skövde Artificial Intelligence Lab (SAIL)

Publikations- och innehållstyp

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