Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/22377
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dc.contributor.authorGievska, Sonjaen_US
dc.contributor.authorLameski, Petreen_US
dc.date.accessioned2022-08-17T09:57:06Z-
dc.date.available2022-08-17T09:57:06Z-
dc.date.issued2017-07-09-
dc.identifier.urihttp://hdl.handle.net/20.500.12188/22377-
dc.description.abstractThe model representing the complexity of the pedestrian mobility has to incorporate the nature of the modeled phenomenon by accounting the interde‐ pendence between human behavior and urban environment. Our efforts are directed towards correlating emergent behavior patterns of different types of pedestrians to contextual knowledge that will help us map realistic pedestrian behavior into agent’s decision making capabilities. We propose that agent’s beliefs, goals and decision-making strategies should be derived directly from the integrated urban knowledge. Causal probabilistic models that are based on Baye‐ sian inference are proposed as a potential solution to some of the challenges in the pedestrian agent modeling.en_US
dc.publisherSpringer, Chamen_US
dc.subjectPedestrian modeling · Bayesian inference · Multi-agent simulationen_US
dc.titleKnowledge-Based Approach to Modeling Urban Dynamicsen_US
dc.typeProceeding articleen_US
dc.relation.conferenceInternational Conference on Distributed, Ambient, and Pervasive Interactionsen_US
item.grantfulltextopen-
item.fulltextWith Fulltext-
crisitem.author.deptFaculty of Computer Science and Engineering-
crisitem.author.deptFaculty of Computer Science and Engineering-
Appears in Collections:Faculty of Computer Science and Engineering: Conference papers
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