Freksa, Christian, Ph.D.Colonius, ImmoImmoColonius2020-03-092020-03-092015-09-02https://media.suub.uni-bremen.de/handle/elib/952Understanding complex behaviours is an essential component of everyday life, integrated into daily routines as well as specialised research. To handle the increasing amount of data available from (logistic) dynamic scenarios, analysis of the behaviour of agents in a given environment is becoming more automated and thus requires reliable new analytical methods. This thesis seeks to improve analysis of observed data in dynamic scenarios by developing a new model for transforming sparse behavioural observations into realistic explanations of agent behaviours, with the goal of testing that model in a real-world maritime navigation scenario.eninfo:eu-repo/semantics/openAccessProcess RecognitionPattern MatchingMulti-Agent-SystemsArtificial Intelligence (AI)Cognitive ReasoningSpatial-Temporal ReasoningSpatial ReasoningLocalization TasksQualitative Spatial Reasoning (QSR)Knowledge RepresentationPlanning and Plan RecognitionQualitative Reasoning (QR)LogicsInference SystemsLinear Temporal Logic (LTL)000Dissertationurn:nbn:de:gbv:46-00104862-13