TY - GEN
T1 - Incorporating a PMF-based injury model into a multi-agent representation of crowd behavior
AU - McKenzie, Frederic D.
AU - Piland, Herbie H.
AU - Min, Song
PY - 2007
Y1 - 2007
N2 - Throughout the years, much research has been conducted on human behavior models that focus on individual intelligent human agents. Fewer multi-agent based models have addressed group or crowd behavior from a psychological and sociological perspective. We have been focused on incorporating crowd behavior models into control force (police and military) simulations and have developed a real-time crowd simulation capable of generating multiple intelligent agent civilians that exhibit a variety of realistic individual and group behaviors at differing levels of fidelity. One important aspect of modeling realistic crowd behaviors is determining the physiological effects of weapons, both non-lethal and lethal alike, on humans. To this end, we present our categories of non-lethal weapons and their physiological effects that need to be represented. Additionally, this paper describes an injury model developed by the University of Pennsylvania and its integration into our Crowd Federate.
AB - Throughout the years, much research has been conducted on human behavior models that focus on individual intelligent human agents. Fewer multi-agent based models have addressed group or crowd behavior from a psychological and sociological perspective. We have been focused on incorporating crowd behavior models into control force (police and military) simulations and have developed a real-time crowd simulation capable of generating multiple intelligent agent civilians that exhibit a variety of realistic individual and group behaviors at differing levels of fidelity. One important aspect of modeling realistic crowd behaviors is determining the physiological effects of weapons, both non-lethal and lethal alike, on humans. To this end, we present our categories of non-lethal weapons and their physiological effects that need to be represented. Additionally, this paper describes an injury model developed by the University of Pennsylvania and its integration into our Crowd Federate.
UR - http://www.scopus.com/inward/record.url?scp=35148842953&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=35148842953&partnerID=8YFLogxK
U2 - 10.1109/SNPD.2007.317
DO - 10.1109/SNPD.2007.317
M3 - Conference contribution
AN - SCOPUS:35148842953
SN - 0769529097
SN - 9780769529097
T3 - Proceedings - SNPD 2007: Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing
SP - 1022
EP - 1027
BT - Proceedings - SNPD 2007
T2 - SNPD 2007: 8th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing
Y2 - 30 July 2007 through 1 August 2007
ER -