Using adaptive multi-agent systems to simulate economic models

Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 2004

Volumn 1, Issue , 2004, Pages 68-75

  Guessoum, Zahia ^a   Rejeb, Lilia ^b   Durand, Rodolphe ^c  

^a SORBONNE UNIVERSITÉ   (France)

^b UNIVERSITÉ DE REIMS CHAMPAGNE ARDENNE   (France)

^c EMLYON BUSINESS SCHOOL   (France)

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTIVE AGENTS; ADAPTIVE MULTI-AGENT SYSTEMS; ECONOMIC MODELS; STRATEGIC MANAGEMENT;

ADAPTIVE SYSTEMS; COMPUTER SIMULATION; LARGE SCALE SYSTEMS; MARKETING; MATHEMATICAL MODELS; SOCIETIES AND INSTITUTIONS;

MULTI AGENT SYSTEMS;

EID: 4544358440     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (17)

1. A. J. A. Baum and H. Rao. Handbook of Organizational Change and Development, chapter Evolutionary Dynamics of Organizational Populations and Communities. Oxford University Press, 1999.
2. E. Bruederer and J. Singh. Organizational evolution, learning, and selection: A genetic algorithm-based model. Academy of management journal, 39(5): 1322-1349, 1996.
3. K. M. Carley, An Introduction to Evolutionary Theories in Economics, chapter Adaptive Organizations and Emergent Form. Springer-Verlag, 1994.
4. K. M. Carley. Adaptive organizations and emergent forms. Organization Science, 769(2-3), 1998.
5. G. Dosi and R. R. Nelson. An introduction to evolutionary theories in economics. Journal of Evolutionary Economics, 4(1):153-172, 1994.
6. R. Durand and Z. Guessoum. Competence systemics and survival, simulation and empirical analysis. In Competence 2000 Conference, pages 10-24, 2000.
7. Z. Guessoum and J.-P. Briot. From active objects to autonomous agents. IEEE Concurrency, 7(3):68-76, 1999.
8. J. Holland, L. B. Booker, M. Colombetti, M. Dorigo, D. E. Godberg, S. Forrest, R. Riolo, R. E. Smith, P.-L. Lanzi, W. Soltzmann, and S. W. Wilson. What is a learning classifier system? in learning classifier systems: from foundations to applications. In P.-L. Lanzi, W. Stolzmann, and S. W. Wilson, editors, Learning Classifier Systems: from Foundations to Applications, pages 3-32. Springer-Verlag, Heidelberg, 2000.
9. T. Kovacs. Evolving optimal populations with XCS classifier systems. Technical Report CSRP-96-17, October 1996.
10. D. A. Levinthal. Adaptation on rugged landscapes. Management Science, 43(7):934-950, 1997.
11. A. Y. Lewin and H. W. Volberda. Prolegomena on coevolution: A framework for research on strategy and new organizational forms. Organization Science, 10(5):519-534, 1999.
12. A. Lomi and E. R. Larsen. Interacting locally and evolving globally: A computational approach to the dynamics of organizational populations. Academy of Management Journal, 39(4):1287-1321, 1996.
13. H. Mizuta and Y. Yamagata, Agent-based simulation for economic and environmental studies. In JSAI 2001 Workshops, number 2243 in LNAI, pages 142-152. Springer Verlag, 2001.
14. R. R. Nelson and S. Winter. An evolutionary theory of economic change. Harvard University Press, Cambridge, 1982.
15. E. Penrose. The theory of the growth of the firm. John Wiley, 1959.
16. S. W. Wilson. Classifier Fitness Based on Accuracy. Evolutionary Computation, 3(2): 149-175, 1995.
17. L. A. Zadeh, A new direction in ai: Toward a computational theory of perceptions. AI Magazine, 22(1):73-84, 2001.