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Average Optimality for Adaptive Markov Control Processes with Unbounded Costs and Unknown Disturbance Distribution

In: Markov Processes and Controlled Markov Chains

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  • J. Adolfo Minjárez-Sosa

    (Universidad de Sonora, Departamento de Matemcáticas)

Abstract

We study the adaptive control problem for a class of discrete-time Markov control processes with Borel state and action spaces, and possibly unbounded one-stage costs. The processes evolve according to recursive equations x t +1 = F(x t , a t ,ξ t ),t = 0, 1,…, with i.i.d. ℜ k — valued random vectors ξ t with unknown distribution. Assuming observability of ξ t , we propose three different sets of conditions each of which allows us to prove average optimality of a type of adaptive control policies.

Suggested Citation

  • J. Adolfo Minjárez-Sosa, 2002. "Average Optimality for Adaptive Markov Control Processes with Unbounded Costs and Unknown Disturbance Distribution," Springer Books, in: Zhenting Hou & Jerzy A. Filar & Anyue Chen (ed.), Markov Processes and Controlled Markov Chains, chapter 0, pages 111-134, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4613-0265-0_7
    DOI: 10.1007/978-1-4613-0265-0_7
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