정보와 통신 (Information and Communications Magazine)

한국통신학회 (The Korean Institute of Commucations and Information Sciences)
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인공재난: 재난 대응을 위한 에이전트 시뮬레이션의 연구동향

  • 발행 : 2012.04.30
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초록

본 연구는 재난으로 인해 발생할 수 있는 피해를 미리 파악하여 대비할 수 있는 새로운 예측 방법론인 인공 재난에 대해 소개한다. 인공 재난은 재난이 발생할 수 있는 지역의 환경, 발생하는 재난의 변화, 재해를 입고 이에 반응하는 사람들의 행동을 설계하여 인위적으로 재난 상황을 실험해 볼 수 있는 에이전트 기반 시뮬레이션 모형이다. 인공 재난은 재해를 최소화하는 의사결정에 결정적인 역할을 하기에 매우 중요하다. 본 연구에서는 인공 재난의 특정과 분류 별 연구(재난 환경 연구, 재난 확산 연구, 재난 대응 연구)를 소개한다. 그리고 현재 정보 통신 인프라 기반 위에서 대용량 자료를 활용한 향후 연구들을 전망한다.

키워드

참고문헌

  1. 강소연, 조정훈, 최선호, 홍민호, 장원복 (2004). "방제시률레이션을 통한 의료시설의 피난안전성 평가", 대한설비공학회 학술발표대회논문집. PP. 1018-1023.
  2. 조준성, 박종승, 이동호 (2008). "건축물 내에서의 군중 피난 시율레이션 시스템 개발", 한국정보과학회 학술발표논문집 35(2), PP. 225-229.
  3. Altay, N., Green III, W.G. (2006). OR/MS research in disaster operations management. European Journal of Operational Research 175. 475-493.
  4. Altshuler, E., Ramos, O., Nunez, Y., Fernandez, J., Batista-Leyva, AJ., Noda, C. (2005). Symmetry breaking in escaping ants. The American Naturalist 166(6). 643-649. https://doi.org/10.1086/498139
  5. AMP Eclipse, http://www.eclipse.org/amp.
  6. Argonne National Laboratory, http://www.anl. gov/ index.html
  7. Borshcev, A., Filippov, A. (2004). From system dynamics and discrete event to practical agent based modeling: reasons, techniques, tools. The 22nd International Conference of the System Dynamics Society.
  8. Bohn, G. A., Richie, C.G. (1970). Learning by simulation. The validation of disaster simulation: medical scheme planning. Journal of Kansas Medical Society 1(11). 418-425.
  9. Bradley GE. (1993). A proposed mathematical model for computer prediction of crowd movements and their associated risks In: Smith RA, Dikie JF, editors. Engineering for crowd safety. Amsterdam: Elsevier 303-311.
  10. Brauer, F., van den Driessche, P., Wu, J. (Eds). Mathematical Epidemiology. Lecture Notes in Mathematics, subseries in Mathematical Biosciences Subseries 1945. 2008.
  11. Braun, A., Bodmann, E., Oliveira, L., Musse, S.(2003). Modeling individual behaviors in crowd simulation. Computer Animation and Social Agents 16th International Conference.
  12. Braun, A., Bodmann, B. and Musse, S. (2005). Simulating virtual crowd in emergency situations. Proceedings of ACM Symposium Virtual Reality Software and Technology. 244-252.
  13. Bush, B.B., Dauelsberg, L. R., LeClaire, R. J., Powell, D. R., DeLand, S.M., Samsa, M.E. (2005). Critical infrastructure protection decision support systems(CIP/DSS) project overview. Los Alamos National Laboratory Report. LA-UR-05-1870.
  14. Carley, K. M., Fridasma, D.B., Casman E., Yahja, A., Altman, N., Chen, L., Kaminsky, B., Nave, D. (2006). BioWar: Scalable agent-based model for bioattacks. IEEE Transactions on Systems, Man, and Cybernetics- Part A: Systems and Humans 36(2) 252-265. https://doi.org/10.1109/TSMCA.2005.851291
  15. The Center for Catastrophe Preparedness & Response, http://www.nyu.edu/ccpr.
  16. Christie, J., Levary, R. R. (1998). The use of simulation in planning the transportation of patients to hospitals following a disaster. Journal of Medical Systems 22(5). 289-300. https://doi.org/10.1023/A:1020521909778
  17. Clinton, W.J. (1996). Executive Order 13010-Critical Infrastructure Protection. Federal Register 61(138). 37347-37350.
  18. Coolahan, J.E., Kane , M.T., Schloman, J.F., Koomullil, R.P., Shih, A.M., Ito, Y., Kaisar, E.I., Walsh, K. K. (2008), Design of an urban chemical disaster simulation federation for preparedness and response. 2007 Spring Simulation Interoperability Workshop (paper 07S-SIW-077).
  19. Conzelmann, G., Boyd, G., Koritarov, V., Veselka, T. (2000). Multi-agent power market simulation using EMCAS. Proceedings of the IEEE PES General Meeting, San Francisco, California.
  20. Dudenhoeffer, D.D., Permann, M.R. (2006). CIMS: a framework for infrastructure interdependency modeling and analysis. Proceedings of the 2006 Winter Simulation Conference.
  21. Edmonds, B., Hales, D. (2003). Replication, replication and replication: some hard lessons from model alignment. Journal of Artificial Societies and Social Simulation 6.
  22. EM-DAT, http://www.emdat.be.
  23. Epstein, J. M. (2009). Modelling to contain pandemics. In: Nature 460(7245). 687. https://doi.org/10.1038/460687a
  24. Fredkin, E., Toffoli, T. (1982). Conservative logic. International Journal of Theoretical Physics 21. 219- 253. https://doi.org/10.1007/BF01857727
  25. Germann, TC. Kadau, K. Longini, IM. Jr., Macken, CA. (2006). Mitigation strategies for pandemic influenza in the United States. Proceedings of National Academic Science USA 103 5935-5940.
  26. Gilbert, N., Troitzsch, K.G. (1999). Simulation for the social scientist. Open University Press, Philadelphia.
  27. Gilbert, N., Jager, W., Deffuant, G., Adjali, I. (2007). Complexities in markets: introduction to the special issue. Journal of Business Research 60. 813-815. https://doi.org/10.1016/j.jbusres.2007.01.016
  28. Global Terrorism Database, http://www.start.umd. edu/gtd.
  29. Goldspink, C. (2002). Methodological implications of complex systems approaches to sociality: simulation as a foundation for knowledge. Journal of Artificial Societies and Social Simulation 5.
  30. Gulpinar, N., Rustem, B., Settergren, R. (2004) . Simulation and optimization approaches to scenario tree generation. Journal of Economic Dynamics & Control 28.1291-1315. https://doi.org/10.1016/S0165-1889(03)00113-1
  31. Henderson, LF. (1971). The statistics of crowd fluids. Nature 229. 381-383. https://doi.org/10.1038/229381a0
  32. Helbing, D., Molnar, P. (1995). Social force model for pedestrian dynamics. Physical Review E 51(5), 4282-4286. https://doi.org/10.1103/PhysRevE.51.4282
  33. Helbing, D., Farkas, I., Vicsek, T. (2000). Simulating dynamical features of escape panic. Nature 407(6803), 487-490. https://doi.org/10.1038/35035023
  34. Huang, C.Y., Sun, C.T., Hsidh, J.L.,Lin, H. (2004). Simulating SARS: Small-World Epidemiological Modeling and Public Health Policy Assessments. Journal of Artificial Societies and Social Simulation 7(4). 2.
  35. Hughes, RL.(2000). The flow of large crowds of pedestrians. Mathematics and Computers in Simulation 53. 367-379. https://doi.org/10.1016/S0378-4754(00)00228-7
  36. Hwang, W.T., Han, M.H., Jeong, H.J, Kim E.H, (2008). A predictive model for a radioactive contamination in an urban environment and its performance capability to the EMRAS project. Journal of Nuclear Science and Technology 5.594-597.
  37. Institute for Homeland Security Solutions, https:// www.ihssnc.org.
  38. International Journal of Critical Infrastructure Protection, http://www.journals.elsevier.com/ international-journal-of -critical-infrastructure-protection/
  39. Journal of Artificial Societies and Social Simulation, http://jasss.soc.surrey.ac.uk/JASSS.html
  40. Kermack, W.O., McKendrick , A.G. (1927). A Contribution to the Mathematical Theory of Epidemics, Proceedings of Royal Society London A 115. 700-721. https://doi.org/10.1098/rspa.1927.0118
  41. Kornhauser, D., Wilensky, U., Rand, W. (2009). Design of guidelines for agent based model. Journal of Artificial Societies and Social Simulation 12(2). 1. http://jasss.soc.surrey.ac.uk/12/2/1.html.
  42. Kotenko I. (2010). Agent-Based Modelling and Simulation of Network Cyber-Attacks and Cooperative Defense Mechanisms. Discrete Event Simulations. 223-246.
  43. Lin , M.C., Manocha, D. (2011). Simulation technologies for evacuation planning and disaster response. Institution for Homeland Security Solutions, https://www.ihssnc.org.
  44. Lo, SM., Huang HC., Wang, P., Yuen, KK. (2006). A game theory based exit selection model for evacuation. Fire Safety Journal 41, 364-369. https://doi.org/10.1016/j.firesaf.2006.02.003
  45. Longini, IM. Jr., Halloran, ME, Nizam, A, Yang, Y. (2004). Containing pandemic influenza with antiviral agents. American Journal of Epidemiology 159. 623- 633. https://doi.org/10.1093/aje/kwh092
  46. Louie, M., Carley, K (2008). Balancing the criticisms: validating multi-agent models of social systems. Simulation Modelling Practice and Theory 16. 242-256. https://doi.org/10.1016/j.simpat.2007.11.011
  47. Madey, G. R., Szabo, G., Barabasi, A. -L. (2006). WIPER: The integrated wireless phone based emergency response system. In V. N. Alexandrov, G. D. val Albada, P. M. A. Sloot, & J. Dongarra (Eds.), Proceedings of the international conference on computational science (3993, 417-424). Berlin, Germany: Springer-Verlag.
  48. MASON, http://mason.gmu.edu.
  49. McKerrow, E. (2003). Understanding WhyDissecting radical Islamist terrorism with agentbased simulation. Los Alamos Science 28. 184-191.
  50. Mylius, S. D., Hagenaars, T.J., Lugner, A.K., Wallinga, J. (2008). Optimal allocation of pandemic influenza vaccine depends on age, risk and timing. Vaccine 26. 3742-3749. https://doi.org/10.1016/j.vaccine.2008.04.043
  51. National Infrastructure Simulation and Analysis, http://www.sandia.gov/nisac/index. html, http:// www.lanl.gov/programs/nisac/index.shtml.
  52. Naizi, M.A., Siddique, Q., Hussain, A., Kolberg, M. (2009). Verification & validation of an agent-based forest fire simulation model. Proceedings of the Agent Directed Simulation Symposium 2010, as part of the ACM SCS Spring Simulation.
  53. Netlogo, http://ccl.northwestern.edu/netlogo.
  54. O'Reilly, G.P., Jrad, A., Kelic, A., LeClaire, R. (2007). Telecom critical infrastructure simulations: discrete event simulation vs. dynamic simulation how do they compare? Proceedings of Global Telecommunications Conference (GLOBECOM). 2597-2601.
  55. Okuyama Y., Sahin S.(2009). Impact Estimation of Disasters: A Global Aggregate for 1960 to 2007, World Bank Policy Research Working Paper No. 4963.
  56. Pederson, P., Dudenhoeffer, D., Hartley, S., Permann, M. (2006). Critical Infrastructure Interdependency Modeling: A Survey of U.S. and International Research, Idaho National Laboratory, USA.
  57. Pelechano N, Allbeck JM, Badler NI. Controlling individual agents in high density crowd simulation. In Metaxas D, Popovic J, editors. (2007). Proceedings of the 2007 ACM SIGGRAPH/Eurographics symposium on computer animation, San Diego, CA, USA, 3-4 August 2007. 99-108.
  58. Repast Suite, http://Repast.sourceforge.net.
  59. Sahin, S. Estimation of Disasters' Economic Impact in 1990-2007: Global Perspectives, Draft (2011).
  60. Saloma, C., Perez, GJ., Tapang, G., Lim M., Palmes-Saloma C., (2003). Self-organized queuing and scale-free behavior in real escape panic. Proceedings of the National Academy of Sciences of the USA (PNAS) 100(21). 11947-11952.
  61. Schoenwand, D.A., Barton, D.C., Ehlen, M. A. (2004). An Agent-based Simulation Laboratory for Economics and Infrastructure Interdependency. Sandia Report.
  62. Swarm Development Group, http://www.swarm.org.
  63. Toroczkai, Z., Eubank, S. (2005). Agent-based modeling as a decision-making tool. The Bridge 35(4). 22-27.
  64. Van Minh, L., Adam, C., Canal, R., Gaudou, B., Vinh, HT., Taillandier, P. (2012). Simulation of the emotion dynamics in a group of agents in an evacuation situation, Principles and practice of multi-agent systems. Lecture Note in Computer Science 7057. 604-619.
  65. Wolfram, S. (1983). Statistical mechanics of cellular automata. Reviews of Modern Physics 55. 601-644. https://doi.org/10.1103/RevModPhys.55.601
  66. Wolfram, S. (1984) Universality and complexity in cellular automata. Physica D 10. 1-35. https://doi.org/10.1016/0167-2789(84)90245-8
  67. Wu, S., Shuman, L., Bidanda, B., Kelley , M., Sochats, K., Balaban, C. (2008). Agent-based Discrete Event Simulation Modeling for Disaster Responses. Proceedings of the 2008 lndustrial Engineering Research Conference.
  68. Wu, S., Shuman, L.J., Bidanda, B., Kelley, M., Lawson, B., Sochats, K., Balaban, C.D. (2007). System implementation issues of dynamic discrete disaster decision simulation system (D4S2)-phase I. Proceedings of the 2007 Winter Simulation conference.
  69. Yang, T., Chou, P. (2005). Solving a multiresponse simulation-optimization problem with discrete variables using a multiple-attribute decision-making method. Mathematics and Computers in Simulation 68. 9-21. https://doi.org/10.1016/j.matcom.2004.09.004
  70. Zenobia, B., Weber, C., Daim. T. (2009). Artificial markets: a review and assessment of a new venue for innovation research. Technovation. 338-350.
  71. Zheng, X., Zhong, T., Liu, M. (2009). Modeling crowd evacuation of a building based on seven methodological approaches . Building and Environment 44 437-445. https://doi.org/10.1016/j.buildenv.2008.04.002
  72. Zoumpoulaki,A., Avradinis. N., Vosinakis, S. (2010). A multi-agent simulation framework for emergency evacuations incorporating personality and emotions. In Artificial Intelligence: Theories, Models and Applications, 6th Hellenic Conference on AI. 423- 428.