On adaptive control of Markov chains using nonparametric estimation

• Autorzy: Ewa Drabik , Łukasz Stettner
• Języki publikacji: EN

Abstrakty

EN

Two adaptive procedures for controlled Markov chains which are based on a nonparametric window estimation are shown.

Słowa kluczowe

EN

controlled Markov chain; estimation; adaptive control

• Wydawca: Institute of Mathematics Polish Academy of Sciences
• Czasopismo: Applicationes Mathematicae
• Rocznik: 2000
• Tom: 27
• Numer: 2
• Strony: 143-152

Daty

wydano

2000

otrzymano

1998-11-13

poprawiono

1999-08-27

Twórcy

autor

Ewa Drabik

• Faculty of Economics, University of Białystok, Warszawska 63, 15-062 Białystok, Poland,

autor

Łukasz Stettner

• Institute of Mathematics, Polish Academy of Sciences, Śniadeckich 8, 00-950 Warszawa, Poland

Bibliografia

• [1] R. Agraval, The continuum-armed bandit problem, SIAM J. Control Optim. 33 (1995), 1926-1951.
• [2] V. S. Borkar, Recursive self-tuning of finite Markov chains, Appl. Math. (Warsaw) 24 (1996), 169-188.
• [3] E. Drabik, On nearly selfoptimizing strategies for multiarmed bandit problems with controlled arms, ibid. 23 (1996), 449-473.
• [4] T. Duncan, B. Pasik-Duncan and Ł. Stettner, Discretized maximum likelihood and almost optimal adaptive control of ergodic adaptive models, SIAM J. Control Optim. 36 (1998), 422-446.
• [5] T. Duncan, B. Pasik-Duncan and Ł. Stettner, Adaptive control of discrete Markov processes by the method of large deviations, in: Proc. 35th IEEE CDC, Kobe 1996, IEEE, 360-365.
• [6] O. Hernández-Lerma and R. Cavazos-Cadena, Density estimation and adaptive control of Markov processes; average and discounted criteria, Acta Appl. Math. 20 (1990), 285-307.
• [7] A. Nowak, A generalization of Ueno's inequality for n-step transition probabilities, Appl. Math. (Warsaw) 25 (1998), 295-299.