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Ana Cristina Bicharra
Universidade Federal Fluminense
Brazil
Nayat Sanchez-Pi
Universidade Federal Fluminense
Brazil
Luis Correia
Universidade de Lisboa
Portugal
José Manuel Molina
Universidad Carlos III de Madrid
Spain
Vol. 1 No. 3 (2012), Articles, pages 69-73
DOI: https://doi.org/10.14201/ADCAIJ20121316973
Accepted: Jun 21, 2013
Copyright

Abstract

This paper presents a multi-agent framework using Net- Logo to simulate human and collective behaviors during emergency evacuations. Emergency situation appears when an unexpected event occurs. In indoor emergency situation, evacuation plans defined by facility manager explain procedure and safety ways to follow in an emergency situation. A critical and public scenario is an airportwhere there is an everyday transit of thousands of people. In this scenario the importance is related with incidents statistics regarding overcrowding and crushing in public buildings. Simulation has the objective of evaluating building layouts considering several possible configurations. Agents could be based on reactive behavior like avoid danger or follow other agent, or in deliberative behavior based on BDI model. This tool provides decision support in a real emergency scenario like an airport, analyzing alternative solutions to the evacuation process.

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References

ANDERSON, G., and Moore, G. 1985. A linear algebraic procedure for solving line- ar perfect foresight models. Eco-nomics letters 17(3):247–252. Spain

BRATMAN, M., and Intentions, P. Practical reason. 1987.

BRAUN, A.; Musse, S.; de Oliveira, L.; and Bodmann, B. 2003. Modeling individu- al behaviors in crowd simulation. In Computer Animation and Social Agents, 2003. 16th International Conference on, 143–148. IEEE.

DAVIDSSON, P. Agent based social simulation: A computer science view. Journal of artificial societies and social simulation 5(1). 2002.

FILIPPOUPOLITIS, A.; Hey, L.; Loukas, G.; Gelenbe, E.; and Timotheou, S. Emer- gency response simulation using wireless sensor networks. In Proceedings of the 1st international conference on Ambient media and systems, ICST (Institute for Com- puter Sciences, Social-Informatics and Telecommunications Engineering). 2008. KINNY, D., and George, M. Commitment and e effectiveness of situated agents. In Proceedings of the twelfth international joint conference on artificial intelligence (IJCAI-91), 82–88. 1991

NEWELL, A., and Simon, H. 1961. Computer simulation of human thinking. Rand Corp.

NEWELL, A., and Simon, H. 1972. Human information processing. Annu. Rev. Psychol. l974 25.

PAN, X.; Han, C.; Dauber, K.; and Law, K. A multiagent based framework for the simulation of human and social behaviors during emergency evacuations. AI & Soci- ety 22(2):113–132. 2007.

RAO, A.; Georgeff, M.; et al. 1995. Bdi agents: From theory to practice. In Proceed- ings of the first international conference on multi-agent systems (ICMAS-95), 312–319. San Francisco. 1995.

Zhan, B.; Monekosso, D.; Remagnino, P.; Velastin, S.; and Xu, L. Crowd analysis: a survey. Machine Vision and Applications 19(5):345–357. 2008.