Symbiotic adaptive multisimulation: An autonomic simulation framework for real-time decision support under uncertainty

ACM Transactions on Modeling and Computer Simulation

Volumn 19, Issue 1, 2008, Pages

  Mitchell, Bradley ^a   Yilmaz, Levent ^a  

^a AUBURN UNIVERSITY   (United States)

Author keywords

Agent simulation; Decision support; Robust intelligence; Uncertainty

Indexed keywords

AGENT SIMULATION; ATTACK MODEL; DECISION SUPPORT; DECISION SUPPORTS; PHYSICAL SYSTEMS; PLAUSIBLE MODEL; ROBUST INTELLIGENCE; SAMS; SEARCH BEHAVIOR; SIMULATION FRAMEWORK; UNCERTAIN ENVIRONMENTS; UNCERTAINTY;

DECISION SUPPORT SYSTEMS;

SIMULATORS;

EID: 67549132890     PISSN: 10493301     EISSN: 15581195     Source Type: Journal    
DOI: 10.1145/1456645.1456647     Document Type: Article

References (33)

1. BANKES, S. 1993. Exploratory modeling for policy analysis. Oper. Res. 43, 1, 435-449.
2. BANKES, S. 1998. Policy analysis for complex and uncertain systems through computational experiments. Proceedings of the IEEE Aerospace Conference, 125-132.
3. BARTON, R. R. 2004. Designing simulation experiments. In Proceedings of the Winter Simulation Conference. Washington, DC, 73-79.
4. BIGELOW, J. H. AND DAVIS, P. K. 1999. Experiments in Multiresolution Modeling (MRM). RAND, Santa Monica, CA.
5. BRATTON, D. AND KENNEDY, J. 2007. Defining a standard for particle swarm optimization. In Proceedings of the IEEE Swarm Intelligence Symposium. IEEE, 120-127.
6. BRAUDE, E. J. 2004. Software Design: From Programming to Architecture. John Wiley & Sons.
7. COLLIER, T. C. AND TAYLOR, C. 2004. Self-organization in sensor networks. J. Para. Distrib. Comput. 64, 7.
8. CROWTHER, B. 2004. Flocking of autonomous unmanned air vehicles. Aeron. J. 107, 1068, 111-124.
9. DAVIS, P. K. AND BIGELOW, J. H. 1988. The role of uncertainty in assessing the nato-pact central region balance. RAND N-2839. RAND, Santa Monica, CA.
10. DAVIS, P. K. AND BIGELOW, J. H. 2000. Exploratory analysis enabled by multiresolution, multiperspective modeling. Proceedings of the Winter Simulation Conference, 127-134.
11. DEJONG, K. A. 2006. Evolutionary Computation: A Unified Approach. MIT Press, Cambridge, MA.
12. DREO, J., PETROWSKI, A., SIARRY, P., AND TAILLARD, E. 2006. Metaheuristics for Hard Optimization: Methods and Case Studies. Springer-Verlag, Berlin, Germany.
13. EPSTEIN, J. M. 2006. Generative Social Science: Studies in Agent-Based Computational Modeling. Princeton University Press, Princeton, NJ.
14. EPSTEIN, J. M. AND AXTELL, R. L. 1996. Growing Artificial Societies: Social Science from the Bottom Up. The MIT Press, Cambridge, MA.
15. FOGEL, D. B. 2006. Evolutionary computation: Toward a New Philosophy of Machine Intelligence. John Wiley & Sons, Hoboken, N J.
16. F UJIMOTO, R. M., LUNCEFORD, D., PAGE, E., AND UHRMACHER, A. M. 2002. Grand challenges for modeling and simulation: Dagstuhl report.
17. GOLDBERG, D. E. 1989. Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley, Reading, MA.
18. HENDERSON, S. G. 2003. Input model uncertainty: Why do we care and what should we do about it? In Proceedings of the Winter Simulation Conference, 90-97.
19. HOLLAND, J. H. 1975. Adaptation in Natural and Artificial Systems. The University of Michigan Press, Ann Arbor, MI.
20. KENNEDY, J. AND EBERHART, R. C. 2001. Swarm Intelligence. Morgan Kaufmann Publishers, San Francisco, CA.
21. LOW, M. Y. H., LYE, K. W., LENDERMANN, P., TURNER, S. J., CHIM, R. T. W., AND LEO, S. H. 2005. An agent-based approach for managing symbiotic simulation of semiconductor assembly and test operation. In Proceedings of the Fourth International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS). ACM Press, New York, NY, 85-92.
22. LOZANO, M. G., KAMRANI, F., AND MORADI, F. 2006. Symbiotic simulation (s2) based decision support. Tech. rep., Swedish Defence Research Agency (FOI).
23. LUA, C. A., ALTENBURG, K., AND NYGARD, K E. 2003. Synchronized multi-point attack by autonomous reactive vehicles with simple local communication. In Proceedings of the IEEE Swarm Intelligence Symposium (SIS). IEEE, 95-102.
24. MILLER, J. H. and Page, S. E. 2007. Complex Adaptive Systems: An Introduction to Computational Models of Social Life. Princeton University Press, Princeton, NJ.
25. NAMATAME, A. AND SASAKI, T. 1998. Self-organization of complex adaptive systems as a society of rational agents. Artif Life Robotics 2, 4, 189-195.
26. PRICE, I. C. 2006. Evolving self-organized behavior for homogeneous and heterogeneous UAV or UCAV swarms. M.S. thesis, Air Force Institute of Technology, Wright-Patterson Air Force Base,
27. REYNOLDS, C. 1999. Steering behaviors for autonomous characters. http://www.red3d.com/cwr/papers/1999/gdc99steer.html.
28. WIKI. 2007. The compound eye. http://en.wikipedia.org/wiki/ Compoundeye.
29. YILMAZ, L. 2004. Dynamic model updating in simulation with multimodels: A taxonomy and a generic agent-based architecture. In Proceedings of the Summer Computer Simulation Conference (SCSC), 3-8.
30. YILMAZ, L. 2007. Toward next generation simulation-based computational tools for conflict and peace studies. Soc. Sci. Comput. Rev. 25, 1, 48-60.
31. YILMAZ, L., LIM, A., BOWEN, S., AND OREN, T. 2007. Requirements and design principles for multisimulation with multiresolution, multistage models. In Proceedings of the Winter Simulation Conference.
32. YILMAZ, L., ÖREN, T. I., AND GHASEM-AGHAEE, N. 2006. Simulation-based problem-solving environments for conflict studies. Simul. Gam. J. 37, 4, 534-556.
33. ZEIGLER, B. P. 1989. Discrete event abstraction: an emerging paradigm for modeling complex adaptive systems. In Perspectives on Adaptation in Natural and Artificial Systems, Essays in Honor of John Holland. Sante Fe Institute, Oxford University Press, UK.