Distributed dynamic reinforcement of efficient outcomes in multiagent coordination

2007 European Control Conference, ECC 2007

Volumn , Issue , 2007, Pages 2505-2512

  Chasparis, Georgios C ^a   Shamma, Jeff S ^a  

^a University of California   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CONTROL ENGINEERING;

CONVERGENCE PROPERTIES; COORDINATION STRUCTURES; DERIVATIVE FEEDBACKS; DISTRIBUTED DYNAMICS; DISTRIBUTED SYSTEMS; MULTI-AGENT COORDINATIONS; MULTI-AGENT ENVIRONMENT; UNKNOWN ENVIRONMENTS;

MULTI AGENT SYSTEMS;

EID: 84927739360     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.23919/ecc.2007.7069003     Document Type: Conference Paper

References (25)

1. K. Najim and A. S. Poznyak, Learning Automata: Theory and Applications. Pergamon Press Inc, 1994.
2. A. Jadbabaie, J. Lin, and S. A. Morse, "Coordination of groups of mobile agents using nearest neighbor rules," IEEE Transactions on Automatic Control, vol. 48, no. 6, pp. 988-1001, June 2003.
3. V. D. Blondel, J. M. Hendrickx, A. Olshevsky, and J. N. Tsitsiklis, "Convergence in multiagent coordination, consensus, and flocking," in Proceedings of the 44th IEEE Conference on Decision and Control, Seville, Spain, Dec. 2005, pp. 2996-3000.
4. L. Moreau, "Stability of multiagent systems with time-dependent communication links," IEEE Transactions on Automatic Control, vol. 50, no. 2, pp. 169-182, Feb. 2005.
5. R. Olfati-Saber, J. A. Fax, and R. M. Murray, "Consensus and cooperation in networked multi-agent systems," in Proceedings of the IEEE (to appear), 2007.
6. S. H. Strogatz, Sync: The Emerging Science of Spontaneous Order. New York, NY: Hyperion, 2003.
7. R. Olfati-Saber, "Flocking for multi-agent dynamic systems: Algorithms and theory," IEEE Transactions on Automatic Control, vol. 51, no. 3, pp. 401-420, 2006.
8. M. Kandori, G. Mailath, and R. Rob, "Learning, mutation, and longrun equilibria in games," Econometrica, vol. 61, pp. 29-56, 1993.
9. H. P. Young, "The evolution of conventions," Econometrica, vol. 61, pp. 57-84, 1993.
10. -, Individual Strategy and Social Structure. Princeton, NJ: Princeton University Press, 1998.
11. V. Bala and S. Goyal, "A noncooperative model of network formation," Econometrica, vol. 68, no. 5, pp. 1181-1229, 2000.
12. B. Dutta and M. Jackson, "The stability and efficiency of directed communication networks," Review of Economic Design, vol. 5, pp. 251-272, 2000.
13. D. Fudenberg and D. K. Levine, The Theory of Learning in Games. Cambridge, MA: MIT Press, 1998.
14. J. Shamma and G. Arslan, "Dynamic fictitious play, dynamic gradient play, and distributed convergence to Nash equilibria," IEEE Transactions on Automatic Control, vol. 50, no. 3, pp. 312-327, Mar. 2005.
15. I. K. Cho and A. Matsui, "Learning aspiration in repeated games," Journal of Economic Theory, vol. 124, pp. 171-201, 2005.
16. R. Sutton and A. Barto, Reinforcement learning: An introduction. Cambridge, MA: MIT Press, 1998.
17. W. B. Arthur, "Competing technologies, increasing returns, and lockin by historical events," The Economic Journal, vol. 99, pp. 116-131, 1989.
18. -, "On designing economic agents that behave like human agents," Journal of Evolutionary Economics, vol. 3, pp. 1-22, 1993.
19. B. Skyrms and R. Pemantle, "A dynamic model of social network formation," Proc. of the National Academy of Sciences of the USA, vol. 97, pp. 9340-9346, 2000.
20. K. Verbeeck, A. Nowe, T. Lenaerts, and J. Parent, "Learning to reach the Pareto optimal Nash equilibrium as a team," in AI2002 Advances in Artificial Intelligence, ser. LNCS, R. McKay and J. Slaney, Eds. Springer-Verlag, 2002, vol. 2557.
21. X. Wang and T. Sandholm, "Learning near-Pareto-optimal conventions in polynomial time," in Neural Information Processing Systems: Natural and Synthetic (NIPS), 2003.
22. K. Narendra and M. Thathachar, Learning Automata: An introduction. Prentice-Hall, 1989.
23. N. Williams, "Escape dynamics in learning models," Ph. D. dissertation, University of Chicago, 2001.
24. M. J. Osborne and A. Rubinstein, A Course in Game Theory. Cambridge, MA: MIT Press, 1994.
25. H. J. Kushner and G. G. Yin, Stochastic Approximation Algorithms and Applications. Springer-Verlag New York, Inc., 1997.