|
1. T. Bosse, R. Duell, Z. A. Memon, et al, “Agent-Based Modeling of Emotion Contagion in Groups,” Cognitive Computation, vol. 7, no. 1, pp. 111-136, 2015
|
|
2. A. A. Bakar, M. A. Majid, K. Hammad, “An Overview of Crowd Evacuation Simulation,” Advanced Science Letters, vol. 4, no. 2, pp. 400-407, 2016
|
|
3. T. Bosse, M. Hoogendoorn, M. C. Klein, et al, “Modelling Collective Decision Making in Groups and Crowds: Integrating Social Contagion and Interacting Emotions, Beliefs and Intentions,” Autonomous Agents and Multi-Agent Systems, vol. 27, no. 1, pp. 52-84, 2013
|
|
4. D. Centola, “The Spread of Behavior in an Online Social Network Experiment,” Science, vol. 329, no. 5996, pp. 1194-7, 2010
|
|
5. J. Gratch, L. Cheng, S. Marsella, “The Appraisal Equivalence Hypothesis: Verifying The Domain-Independence of a Computational Model of Emotion Dynamics,” International Conference on Affective Computing and Intelligent Interaction. IEEE, pp. 105-111, 2015
|
|
6. S. Kim, S. J.Guy, D. Manocha, et al, “Interactive Simulation of Dynamic Crowd Behaviors Using General Adaptation Syndrome Theory,” ACM SIGGRAPH Symposium on Interactive 3d Graphics and Games, pp. 55-62, 2012
|
|
7. Z. Meng, X. Fu, “Dynamic Information Spreading Model Based on Online Social Network,” Journal of Computer Applications, vol. 34, no. 7, pp. 1960-1963, 2014
|
|
8. F. Martinez-Gil, M. Lozano, F. Fernández, “Strategies for Simulating Pedestrian Navigation with Multiple Reinforcement Learning Agents,” Autonomous Agents and Multi-Agent Systems, vol. 29, no. 1, pp. 98-130, 2015
|
|
9. F. Martinez-Gil, M. Lozano, F. Fernández, “MARL-Ped: A Multi-Agent Reinforcement Learning Based Framework to Simulate Pedestrian Groups,” Simulation Modelling Practice & Theory, vol. 47, no. 47, pp. 259-275, 2014
|
|
10. Y. Moreno, M. Nekovee, A. F. Pacheco, “Dynamics of Rumor Spreading in Complex Networks,” Physical Review E Statistical Nonlinear & Soft Matter Physics, vol. 69, pp. 066130, 2004
|
|
11. S. Navlakha, C. Faloutsos, Z. Bar-Joseph, “MassExodus: Modeling Evolving Networks in Harsh Environments,” Data Mining & Knowledge Discovery, vol. 29, no. 5, pp. 1211-1232, 2015
|
|
12. M. Nekovee, Y. Moreno, G. Bianconi, et al, “Theory of Rumour Spreading in Complex Social Networks,” Physica A Statistical Mechanics & Its Applications, vol. 374, no. 1, pp. 457-470, 2007
|
|
13. A. A. Ojugo, B. E. Iwhiwhu, D. Kekeje, et al, “Malware Propagation on Social Time Varying Networks: A Comparative Study of Machine Learning Frameworks,” International Journal of Modern Education & Computer Science, vol. 6, no. 8, 2014
|
|
14. B. A. Prakash, H. Tong, N. Valler, et al, “Virus Propagation on Time-Varying Networks: Theory and Immunization Algorithms,” American Journal of Medicine, vol. 73, no. 1A, pp. 300-4, 2010
|
|
15. D. P. Papadopoulos, “Cellular Automaton Model of Crowd Evacuation Inspired by Slime Mould,” International Journal of General Systems, vol. 44, no. 3, pp. 354-391, 2015
|
|
16. J. E. Steephen, “HED: A Computational Model of Affective Adaptation and Emotion Dynamics,” IEEE Transactions on Affective Computing, vol. 4, no. 2, pp. 197-210, 2013
|
|
17. M. R. Sanatkar, W. N. White, B. Natarajan, et al, “Epidemic Threshold of an SIS Model in Dynamic Switching Networks,” IEEE Transactions on Systems Man & Cybernetics Systems, vol. 46, no. 3, pp. 345-355, 2016
|
|
18. L. Tan, M. Hu, H. Lin, “Agent-based Simulation of Building Evacuation: Combining Human Behavior with Predictable Spatial Accessibility in a Fire Emergency,” Information Sciences, vol. 295, pp. 53-66, 2015
|
|
19. D. Thalmann, S. R. Musse, “Crowd Simulation,” Springer Publishing Company, Incorporated, 2012
|
|
20. N. Xiang, Z. Pan, L. Zhu, et al, “Dynamic Crowd Emotion Contagion Simulation with GPU Acceleration,” International Conference on Cyberworlds, IEEE Computer Society, pp. 175-178, 2016
|
|
21. X. Yang, H. Dong, Q. Wang, et al, “Guided crowd dynamics via modified social force model,” Physica A Statistical Mechanics & Its Applications, vol. 411, no. 10, pp. 63-73, 2014
|
|
22. W. Zeng, H. Nakamura, and P. Chen, “A Modified Social Force Model for Pedestrian Behavior Simulation at Signalized Crosswalks,” Procedia - Social and Behavioral Sciences , vol. 138, pp. 521-530, 2014
|
|
23. B. Zhou, X. Tang, X. Wang, “Learning Collective Crowd Behaviors with Dynamic Pedestrian-agents,” International Journal of Computer Vision, vol. 111, no. 1, pp. 50-68, 2015
|
|
24. L. Zhao, J. Wang, Y. Chen, et al, “SIHR Rumor Spreading Model in Social Networks,” Physica A Statistical Mechanics & Its Applications, vol. 391, no. 7, pp. 2444-2453, 2012
|
|
25. D. Zhao, J. Wang, X. Zhang, et al, “A Cellular Automata Occupant Evacuation Model Considering Gathering Behavior,” International Journal of Modern Physics C , vol. 26, no. 08, pp. 1550089, 2015
|
|
26. D. Zhao, B. Yegenmammedov, P. Liu, et al, “Comparative Study on Occupant Evacuation with Building EXODUS and a Cellular Automaton Model,” Open Journal of Safety Science & Technology, vol. 07, no. 1, pp. 42-57, 2017
|