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

J. Adolfo Minjárez-Sosa ()
Additional contact information
J. Adolfo Minjárez-Sosa: Universidad de Sonora, Departamento de Matemcáticas

Chapter Chapter 7 in Markov Processes and Controlled Markov Chains, 2002, pp 111-134 from Springer

Abstract: 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.

Keywords: Markov control process; discounted and average cost criteria; adaptive control policies (search for similar items in EconPapers)
Date: 2002
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4613-0265-0_7

Ordering information: This item can be ordered from
http://www.springer.com/9781461302650

DOI: 10.1007/978-1-4613-0265-0_7

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().