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Authors: Pejman Kamkarian and Henry Hexmoor

Affiliation: Southern Illinois University, United States

Keyword(s): Networks of Bayesian Belief Revision, Public Space Safety, Crowd Evacuation.

Related Ontology Subjects/Areas/Topics: Agents ; Artificial Intelligence ; Collective Intelligence ; Knowledge Representation and Reasoning ; Symbolic Systems

Abstract: This paper demonstrates a solution for analyzing public space evacuation rates. Evacuating from a public building in a reasonable amount of time is reliant upon how safe the space is in terms of achieving a minimum time to move people outside. In order to increase the safety of evacuation in public spaces, we employed the Bayesian Belief Network method. To have a better estimation pattern, we have to focus on important physical environmental features as well as crowd formation and specifications in a public space.

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Paper citation in several formats:
Kamkarian, P. and Hexmoor, H. (2013). Predicting Evacuation Capacity for Public Buildings. In Proceedings of the 5th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-8565-39-6; ISSN 2184-433X, pages 433-440. DOI: 10.5220/0004217704330440

@conference{icaart13,
author={Pejman Kamkarian. and Henry Hexmoor.},
title={Predicting Evacuation Capacity for Public Buildings},
booktitle={Proceedings of the 5th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2013},
pages={433-440},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004217704330440},
isbn={978-989-8565-39-6},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 5th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Predicting Evacuation Capacity for Public Buildings
SN - 978-989-8565-39-6
IS - 2184-433X
AU - Kamkarian, P.
AU - Hexmoor, H.
PY - 2013
SP - 433
EP - 440
DO - 10.5220/0004217704330440

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