Skip to main content

On learning automata

  • Chapter
  • First Online:
Learning Automata and Stochastic Optimization

Part of the book series: Lecture Notes in Control and Information Sciences ((LNCIS,volume 225))

  • 158 Accesses

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Wiener N 1948 Cybernetics. The Technology Press John Wiley, New York

    Google Scholar 

  2. Bellman R 1973 Adaptive Control Processes-A Guided Tour. Princeton University Press, Princeton

    Google Scholar 

  3. K.J. Åström K J, Wittenmark B 1984 Computer Controlled Systems Theory and Design. Prentice-Hall, Englewood Cliffs

    Google Scholar 

  4. Najim K 1988 Control of Liquid-Liquid Extraction Columns. Gordon and Breach, London

    Google Scholar 

  5. Tsetlin M L 1973 Automaton Theory and Modeling of Biological Systems. Academic Press, New York

    Google Scholar 

  6. Narendra K S, Thathachar M A L 1989 Learning Automata an Introduction. Prentice-Hall, Englewood Cliffs

    Google Scholar 

  7. Baba N 1984 New Topics in Learning Automata Theory and Applications. Springer-Verlag, Berlin

    Google Scholar 

  8. Najim K, Oppenheim G 1991 Learning systems: theory and applications. IEE Proceedings Computer and Digital Techniques 138:183–192

    Google Scholar 

  9. Najim K, Poznyak A S 1994 Learning Automata: Theory and Applications. Pergamon Press, Oxford

    Google Scholar 

  10. Walter W G 1953 The Living Brain. Norton, New York

    Google Scholar 

  11. Caudill M, Butler C 1990 Naturally Intelligent Systems. MIT Press, Cambridge

    Google Scholar 

  12. Najim K 1989 Process Modeling and Control in Chemical Engineering. Marcel Dekker, New York

    Google Scholar 

  13. Tsypkin Ya Z 1971 Adaptation and Learning in Automatic Systems. Academic Press, New York

    Google Scholar 

  14. Pathak-Pal A, Pal S K 1987 Learning with mislabeled training samples using stochastic approximation. IEEE Transactions on Systems, Man, and Cybernetics 17:1072–1077

    Google Scholar 

  15. Zurada J M 1992 Artificial Neural Systems. West Publishing Company, New York

    Google Scholar 

  16. Srikantakumar P R, Narendra K S 1982 A learning model for routing in telephone networks. SIAM J. Control and Optimization 20:34–57

    Google Scholar 

  17. Barto A, Anandan P, Anderson C W 1986 Cooperatively in networks of pattern recognizing stochastic learning automata. In: Narendra K S (ed) 1986 Adaptive and Learning Systems: Theory and Applications. Plenum Press, New York

    Google Scholar 

  18. Narendra K S, Viswanathan R 1972 A two-level system of stochastic automata for periodic random environments. IEEE Trans. Syst. Man, and Cybern. 2:285–289

    Google Scholar 

  19. Nedzelnitsky O V Jr, Narendra K S 1987 Nonstationary models of learning automata routing in data communication networks. IEEE Trans. Syst. Man, and Cybern. 17:1004–1015

    Google Scholar 

  20. Narendra K S, Thathachar M A L 1980 On the behavior of learning automata in a changing environment with application to telephone traffic routine. IEEE Trans. Syst. Man, and Cybern. 10:262–269

    Google Scholar 

  21. Koditschek D E, Narendra K S 1977 Fixed structure automata in a multi-teacher environment. IEEE Trans. Syst. Man, and Cybern. 7:616–624

    Google Scholar 

  22. Baba N, Mogami Y 1988 Learning behaviours of hierarchical structure of stochastic automata in a nonstationary multi-teacher environment. Int. J. Systems Sci. 19:1345–1350

    Google Scholar 

  23. Thathachar M A L, Ramakrishnan K R 1981 A hierarchical system of learning automata. IEEE Trans. Syst. Man, and Cybern. 11:236–241

    Google Scholar 

  24. Poznyak A S, Najim K 1997 On the behaviour of learning automata in nonstationary environments. to appear in European Journal of Control.

    Google Scholar 

  25. Baba N 1983 The absolutely expedient nonlinear reinforcement schemes under the unknown multiteacher environment. IEEE Trans. Syst. Man, and Cybern. 13:100–107

    Google Scholar 

  26. Baba N 1983 On the learning behaviours of variable-structure stochastic automaton in the general N-teacher environment. IEEE Trans. Syst. Man, and Cybern. 13:224–231

    Google Scholar 

  27. Thathachar M A L, Harita B R 1987 Learning automata with changing number of actions. IEEE Trans. Syst. Man, and Cybern. 17:1095–1100

    Google Scholar 

  28. Najim K, Poznyak A S 1996 Multimodal searching technique based on learning automata with continuous input and changing number of actions. IEEE Trans. on Systems, Man, and Cybernetics 26:666–673

    Google Scholar 

  29. Doob J L 1953 Stochastic Processes. John Wiley & Sons, New York

    Google Scholar 

  30. Robbins H, Siegmund D 1971 A convergence theorem for nonnegative almost supermartingales and some applications. In: Rustagi J S (ed) 1971 Optimizing Methods in Statistics. Academic Press, New York

    Google Scholar 

  31. Nazin A V, Poznyak A S 1986 Adaptive Choice of Variants. (in Russian) Nauka, Moscow

    Google Scholar 

  32. Neveu J 1975 Discrete-Parameter Martingales. North-Holland Publishing, Amsterdam

    Google Scholar 

  33. Bush R R, Mosteller F 1958 Stochastic Models for Learning. John Wiley & Sons, New York

    Google Scholar 

  34. Poznyak A S 1975 Investigation of the convergence of algorithms for the functioning of learning stochastic automata. Automation and Remote Control 36:77–91

    Google Scholar 

  35. Kiefer J, Wolfowitz J 1952 Stochastic estimation of the maximum of a regression function,” Ann. Math. Stat. 23:462–466

    Google Scholar 

  36. Shapiro I J, Narendra K S 1969 Use of stochastic automata for parameter self optimization with multimodal performance criteria. IEEE Trans. Syst. Man, and Cybern. 5:352–361

    Google Scholar 

  37. Varshavskii V I, Vorontsova I P 1963 On the behavior of stochastic automata with variable structure. Automation and Remote Control 24:327–333

    Google Scholar 

  38. Narendra K S, Parthasarathy K 1991 Learning automata approach to hierarchical multiobjective analysis. IEEE Trans. Syst. Man, and Cybern. 21:263–273

    Google Scholar 

  39. Poznyak A S, Najim K, Chtourou M 1996 Learning automata with continuous inputs and their application for multimodal functions optimization. Int. J. of Systems Science 27:87–95

    Google Scholar 

  40. Poznyak A S, Najim K, Chtourou M 1996 Analysis of the behaviour of multilevel hierarchical systems of learning automata and their application for multimodal functions optimization. Int. J. of Systems Science 27:97–112

    Google Scholar 

Download references

Rights and permissions

Reprints and permissions

Copyright information

© 1997 Springer-Verlag London Limited

About this chapter

Cite this chapter

(1997). On learning automata. In: Learning Automata and Stochastic Optimization. Lecture Notes in Control and Information Sciences, vol 225. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0015105

Download citation

  • DOI: https://doi.org/10.1007/BFb0015105

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-76154-9

  • Online ISBN: 978-3-540-40938-0

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics