Advertisement

Why Stratification of Networks Emerges in Innovative Society: Intelligent Poly-Agent Systems Approach

  • Kyoichi Kijima
Article

Abstract

This paper rigorously shows in the framework of poly-agent systems theory that it is very natural for an innovative society to emerge stratification of networks to cope with complexity intelligent decision makers of it have to deal with. Before introducing poly-agent systems theory, I will first refer to empirical observations of emergence of stratification of networks in innovative societies, which motivate this research. I, then, theoretically show that coexistence of both networks and hierarchies is reasonable and inevitable for a tightly interrelated society because it can provide the decision makers with mediation, which is beneficial for the decision makers as well as the society as a whole. Finally, I will go back again to implications from our theoretical study.

innovation poly-agent system emergence social networks 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Auger, P. (1989), Dynamics amd Thermodynamics in Hierarchically Organized Systems: Applications in Physics, Biology and Economics. Pergamon Press, Oxford.Google Scholar
  2. Bennett, P.G. (1980), “Hypergames: Developing a Model of Conflict, ” Futures, 12(6), 489–507.Google Scholar
  3. Bennett, P.G. and M.R. Dando (1979), “Complex Strategic Analysis: A Hypergame Study of the Fall of France, ” J. Opl. Res. Soc., 30(1), 23–32.Google Scholar
  4. Bennett, P.G., M.R. Dando and R.G. Sharp (1980), “Using Hypergames to Model Difficult Social Issues: An Approach to the Case of Soccer Hooliganism, ” J. Opl. Res. Soc., 31(7), 621–635.Google Scholar
  5. Bennett, P.G., S. Cropper and C. Huxham (1989) “Modelling Interactive Decisions: The Hypergame Focus, ” in J. Rosenhead (Ed.) Rational Analysis for a Problematic World. John Wiley and Sons, Chichester.Google Scholar
  6. Carley, K.M. and D.M. Svoboda (1996), “Modeling Organizational Adaptation as a Simulated Annealing Process, ” Sociological Methods and Research, 25(1), 138–168.Google Scholar
  7. Carver, N. and V. Lesser (1994), “The Evolution of Blackboard Control Architectures, ” Expert Systems and Applications, 7(1), 1–30.Google Scholar
  8. Checkland, P.B. (1981), Systems Thinking, Systems Practice. John Wiley, Chichester.Google Scholar
  9. Checkland, P.B. (1990), Soft Systems Methodology in Action. John Wiley, Chichester.Google Scholar
  10. Fraser, N.M. and K.W. Hipel (1984), Conflict Analysis: Models and Resolutions. North-Holland, Amsterdam.Google Scholar
  11. Fraser, N.M., M. Wang and K.W. Hipel (1991), “Hypergame Theory in 2-Person Conflicts, ” Information and Decision Technology, 16, 301–319.Google Scholar
  12. Galbraith, J. (1977), Organization Design. Addison-Wesley, Reading, MA.Google Scholar
  13. Gibbons, R. (1992), A Primer in Game Theory. Harvester Wheatsheaf, London.Google Scholar
  14. Harsanyi, J. (1967), “Games with Incomplete Information played by Bayesian Players, Parts I, II and III, ” Management Science, 14, 159–182, 320–334, 486–502.Google Scholar
  15. Howard, N. (1987), “The Present and Future of Metagame Analysis, ” European Journal of Operational Research, 32, 1–25.Google Scholar
  16. Howard, N. (1989), “The Manager as Politician and General: The Metagame Approach to Analysing Cooperation and Conflict, ” in J. Rosenhead (Ed.) Rational Analysis for aProblematicWorld. JohnWiley and Sons, Chichester.Google Scholar
  17. Howard, N. (1990), “Soft Game Theory, ” Information and Decision Technologies, 16(3), 215–227.Google Scholar
  18. Howard, N. (1994), “Drama Theory and Its Relation to Game Theory: Part One, ” Group Decision and Negotiation, 3, 187–206.Google Scholar
  19. Howard, N., P. Bennett, J. Bryant and M. Bradley (1993), “Manifesto for a Theory of Drama and Irrational Choice, ” Systems Practice, 6(4), 429–434.Google Scholar
  20. Kijima, K. (1991), “Decision Making Based on Subjective Evaluations of Problem Situation, ” T. IEE, Japan 111-C(3), 98–106, in Japanese.Google Scholar
  21. Kijima, K. (1996a), “Intelligent Poly-Agent Learning Model and its Application, ” Information and Systems Engineering, 2, 47–61.Google Scholar
  22. Kijima, K. (1996b), Negotiation and Accommodation. Nikkagiren Publishing Co., Tokyo, in Japanese.Google Scholar
  23. Kijima, K. (1999), “Poly-Agent Systems Theory: Evolution Model and Its Applications, ” in A.M. Castell et al. (Eds.) Synergy Matters: Working With Systems in the 21st Century, in Proceedings of UKSS99 held at Lincoln, UK, Plenum Press, 577–582.Google Scholar
  24. Levitt, R.E., G.P. Cohen, J.C. Kunz, C.I. Nass, T. Christiansen and Y. Jin (1994), “A Theoretical Evaluation of Measures of Organizational Design: Interrelationship & Performance Predictability, ” in K.M. Carley and M.J. Prietula (Eds.) Computational Organization Theory, Lawrence Erlbaum Associates, Hillsdale, NJ.Google Scholar
  25. Mesarovic, M.D. and Y. Takahara (1989), Abstract Systems Theory. Springer Verlag, Berlin.Google Scholar
  26. Neches, R. et al. (1991), “Enabling Technology for Knowledge Sharing, ” AI Magazine, 12(3), 36–56.Google Scholar
  27. Neches, R. (1993), “Knowledge Sharing Effort, ” Research Report, available at http.stanford.edu in /pub/knowledge-sharing/papers.Google Scholar
  28. Nishio, K. (1999), History of Japan. Mainichi Shinnbunn, Tokyo, in Japanese.Google Scholar
  29. Rosenhead, J. (Ed.) (1989), Rational Analysis for Problematic World. John Wiley, Chichester.Google Scholar
  30. Saxenian, A. (1996), Regional Adventure: Culture and Competition in Silicon Valley and Route 128. Harvard University Press.Google Scholar
  31. Simon, H.A. (1962), “The Architecture of Complexity, ” Proceedings of the American Philosophical Society, 106, 467–482.Google Scholar
  32. Suematsu, T. (1997), “Cultural Comparison Between Organizations in Silicon Valley and Japan: An Approach from IT Utilization, ” Journal of Association for Management Informatics, 16(3), 23–40, in Japanese.Google Scholar
  33. Takagi, H. et al. (1995), Societies in Malti-media Age. Nikkagiren Publishing Co., Tokyo, in Japanese.Google Scholar
  34. Van Gigch, J.P. (1991), System Design Modeling and Metamodeling, Plenum Press, New York.Google Scholar
  35. Wang, M., K.W. Hipe and N.M. Frase (1988), “Modeling Misperceptions in Games, ” Journal of Behavior Science, 33, 207–223.Google Scholar
  36. Wang, M. and K.W. Hipe (1992), “Misperception and Bargaining in the Persian GulfWar, ” Control and Cybernetics, 10(2), 1–26.Google Scholar
  37. Wonham, W.N. (1976), “Towards an Abstract Internal Model Principle, ” IEEE Trans. Systems, Man and Cybernetics, IEEE-SMC, 6(11), 735–740.Google Scholar

Copyright information

© Kluwer Academic Publishers 2001

Authors and Affiliations

  • Kyoichi Kijima
    • 1
  1. 1.Dept. of Value and Decision ScienceTokyo Institute of TechnologyTokyoJapan

Personalised recommendations