Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Markov Decision Processes with Restricted Observations: Finite Horizon Model
Date
1993-01-06
Author
Serin, Yaşar Yasemin
Avşar, Zeynep Müge
Metadata
Show full item record
Item Usage Stats
73
views
0
downloads
Cite This
URI
https://hdl.handle.net/11511/73323
Collections
Unverified, Conference / Seminar
Suggestions
OpenMETU
Core
Markov decision processes with restricted observations: Finite horizon case
Serin, Yaşar Yasemin; Avşar, Zeynep Müge (Wiley, 1997-08-01)
In this article we consider a Markov decision process subject to the constraints that result from some observability restrictions. We assume that the state of the Markov process under consideration is unobservable. The states are grouped so that the group that a state belongs to is observable. So, we want to find an optimal decision rule depending on the observable groups instead of the states. This means that the same decision applies to all the states in the same group. We prove that a deterministic optim...
Markov decision processes with rest ricted observations.
Avşar, Zeynep Müge; Department of Industrial Engineering (1992)
Markov Decision Processes Based Optimal Control Policies for Probabilistic Boolean Networks
Abul, Osman; Alhajj, Reda; Polat, Faruk (2004-06-01)
This paper addresses the control formulation process for probabilistic boolean genetic networks. It is a major problem that has not been investigated enough yet. We argue that a monitoring stage is necessary after the control stage for providing guidance about the evolution of the investigated state. For this purpose, we developed methods for generating optimal control policies for each of the following five cases: finite control, infinite control, finite control-infinite monitoring, finite control-finite m...
Markov decision processes under observability constraints
Serin, Yaşar Yasemin (Springer Science and Business Media LLC, 2005-06-01)
We develop an algorithm to compute optimal policies for Markov decision processes subject to constraints that result from some observability restrictions on the process. We assume that the state of the Markov process is unobservable. There is an observable process related to the unobservable state. So, we want to find a decision rule depending only on this observable process. The objective is to minimize the expected average cost over an infinite horizon. We also analyze the possibility of performing observ...
Markov switching cointegration approach to modeling target zone behavior of the exchange rates with an application to FF/DM exchange rate
Gürgenci, Zerrin; Erlat, Haluk; Department of Economics (1999)
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
Y. Y. Serin and Z. M. Avşar, “Markov Decision Processes with Restricted Observations: Finite Horizon Model,” 1993, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/73323.