Abstract
This chapter proposes an integrated multi-agent Belief-Desire-Intention (BDI) model for emergency egress simulation. The systems works in a partially observable environment which contains heterogeneous agents with limited vision range to better and more realistically model humans in real life scenario. Individuals perceive partial information about the environment and other evacuees continuously; a belief set is created accordingly. A pre-constructed set of plans is filtered using the current beliefs to find sub-tasks. The ultimate goal of each agent is to satisfy its desire set. The model has been integrated with a fuzzy logic engine for action speed calculation. Test case scenarios have been created to observe crowd behavior of agents with different knowledge levels and cooperation skills. The reported results are encouraging. They demonstrate the various aspects of the proposed scenario.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
R.W. Perry, A.H. Mushkatel, Disaster Management: Warning Response and Community Relocation. Quorum Books (Greenwood Press, Westport, 1984)
M. Okaya, T. Takahashi, Human relationship modeling in agent-based crowd evacuation simulation, in International Conference on Principles and Practice of Multi-Agent Systems (Springer, Berlin, 2011), pp. 496–507
H.A. Simon, Models of Man: Social and Rational; Mathematical Essays on Rational Human Behavior in Society Setting (Wiley, Hoboken, 1957)
R. Laughery, Computer simulation as tool for studying human-centered systems, in Proceedings of the 30th Conference on Winter Simulation (IEEE Computer Society Press, Washington, 1998), pp. 61–66
R.J. Dawson, R. Peppe, M. Wang, An agent-based model for risk-based flood incident management. Nat. Hazards 59(1), 167–189 (2011)
Y. Bo, W. Cheng, H. Hua, L. Lijun, A multi-agent and pso based simulation for human behavior in emergency evacuation, in 2007 International Conference on Computational Intelligence and Security (IEEE, Piscataway, 2007), pp. 296–300
X. Pan, C.S. Han, K. Dauber, K.H. Law, A multi-agent based framework for the simulation of human and social behaviors during emergency evacuations. AI Soc. 22(2), 113–132 (2007)
J. Was, R. Lubas, Towards realistic and effective agent-based models of crowd dynamics. Neurocomputing 146, 199–209 (2014)
F. Tang, A. Ren, Agent-based evacuation model incorporating fire scene and building geometry. Tsinghua Sci. Technol. 13(5), 708–714 (2008)
A.S. Rao, M.P. Georgeff, Modeling rational agents within a BDI-architecture. KR 91, 473–484 (1991)
M. Schut, M. Wooldridge, S. Parsons, On partially observable MDPs and BDI models, in Foundations and Applications of Multi-Agent Systems (Springer, Berlin, 2002), pp. 243–259
G. Rens, D. Moodley, A hybrid POMDP-BDI agent architecture with online stochastic planning and plan caching. Cogn. Syst. Res. 43, 1–20 (2017)
R. Nair, M. Tambe, Hybrid BDI-POMDP framework for multiagent teaming. J. Artif. Intell. Res. 23, 367–420 (2005)
M.P. Georgeff, F.F. Ingrand, Decision-Making in an Embedded Reasoning System (Citeseer, 1989)
M. d’Inverno, M. Luck, M. Georgeff, D. Kinny, M. Wooldridge, The dMARS architecture: a specification of the distributed multi-agent reasoning system. Auton. Agent. Multi-Agent Syst. 9(1–2), 5–53 (2004)
X. Zhao, Y. Son, BDI-based human decision-making model in automated manufacturing systems. International Journal of Modeling and Simulation28(3), 347–356 (2007)
S. Lee, Y.-J. Son, Integrated human decision making model under belief-desire-intention framework for crowd simulation, in Winter Simulation Conference, 2008. WSC 2008 (IEEE, Piscataway, 2008), pp. 886–894
D. Helbing, A mathematical model for the behavior of pedestrians. Syst. Res. Behav. Sci. 36(4), 298–310 (1991)
H. Liu, B. Liu, H. Zhang, L. Li, X. Qin, G. Zhang, Crowd evacuation simulation approach based on navigation knowledge and two-layer control mechanism. Inf. Sci. 436, 247–267 (2018)
R.G. Reynolds, An introduction to cultural algorithms, in Proceedings of the Third Annual Conference on Evolutionary Programming (World Scientific, Singapore, 1994), pp. 131–139
C. Adam, P. Taillandier, J. Dugdale, B. Gaudou, BDI vs FSM agents in social simulations for raising awareness in disasters: a case study in Melbourne bushfires. Int. J. Inf. Syst. Crisis Res. Manag. 9(1), 27–44 (2017)
M. Valette, B. Gaudou, D. Longin, P. Taillandier, Modeling a real-case situation of egress using BDI agents with emotions and social skills, in PRIMA 2018: Principles and Practice of Multi-Agent Systems (Springer, Cham, 2018), pp. 3–18
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Şahin, C., Alhajj, R. (2020). Crowd Behavior Modeling in Emergency Evacuation Scenarios Using Belief-Desire-Intention Model. In: Kaya, M., Birinci, Ş., Kawash, J., Alhajj, R. (eds) Putting Social Media and Networking Data in Practice for Education, Planning, Prediction and Recommendation. Lecture Notes in Social Networks. Springer, Cham. https://doi.org/10.1007/978-3-030-33698-1_1
Download citation
DOI: https://doi.org/10.1007/978-3-030-33698-1_1
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-33697-4
Online ISBN: 978-3-030-33698-1
eBook Packages: Physics and AstronomyPhysics and Astronomy (R0)