Conţinutul numărului revistei |
Articolul precedent |
Articolul urmator |
1384 2 |
Ultima descărcare din IBN: 2019-02-02 18:37 |
Căutarea după subiecte similare conform CZU |
519.217 (13) |
Probabilitate. Statistică matematică (80) |
SM ISO690:2012 LOZOVANU, Dmitrii, PICKL, Stefan Wolfgang. An Approach for Determining the Optimal Strategies for an Average Markov Decision Problem with Finite State and Action Spaces. In: Buletinul Academiei de Ştiinţe a Republicii Moldova. Matematica, 2018, vol. 86, nr. 1(86), pp. 34-49. ISSN 1024-7696. |
EXPORT metadate: Google Scholar Crossref CERIF DataCite Dublin Core |
Buletinul Academiei de Ştiinţe a Republicii Moldova. Matematica | ||||||
Volumul 86, Numărul 1(86) / 2018 / ISSN 1024-7696 /ISSNe 2587-4322 | ||||||
|
||||||
CZU: 519.217 | ||||||
MSC 2010: 90C15, 90C40. | ||||||
Pag. 34-49 | ||||||
|
||||||
Descarcă PDF | ||||||
Rezumat | ||||||
The average reward Markov decision problem with finite state and action spaces is considered and an approach for determining the optimal pure and mixed stationary strategies for this problem is proposed. We show that the considered problem can be formulated in terms of stationary strategies where the objective function is quasi-monotonic (i. e. it is quasi-convex and quasi-concave) on the feasible set of stationary strategies. Using such a quasi-monotonic programming model with linear constraints we ground algorithms for determining the optimal pure and mixed stationary strategies for the average Markov decision problem. |
||||||
Cuvinte-cheie Markov decision processes, Average optimization criterion, stationary strategies, Optimal strategies. |
||||||
|
Cerif XML Export
<?xml version='1.0' encoding='utf-8'?> <CERIF xmlns='urn:xmlns:org:eurocris:cerif-1.5-1' xsi:schemaLocation='urn:xmlns:org:eurocris:cerif-1.5-1 http://www.eurocris.org/Uploads/Web%20pages/CERIF-1.5/CERIF_1.5_1.xsd' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' release='1.5' date='2012-10-07' sourceDatabase='Output Profile'> <cfResPubl> <cfResPublId>ibn-ResPubl-64583</cfResPublId> <cfResPublDate>2018-07-01</cfResPublDate> <cfVol>86</cfVol> <cfIssue>1</cfIssue> <cfStartPage>34</cfStartPage> <cfISSN>1024-7696</cfISSN> <cfURI>https://ibn.idsi.md/ro/vizualizare_articol/64583</cfURI> <cfTitle cfLangCode='EN' cfTrans='o'>An Approach for Determining the Optimal Strategies for an Average Markov Decision Problem with Finite State and Action Spaces</cfTitle> <cfKeyw cfLangCode='EN' cfTrans='o'>Markov decision processes; Average optimization criterion; stationary strategies; Optimal strategies.</cfKeyw> <cfAbstr cfLangCode='EN' cfTrans='o'><p>The average reward Markov decision problem with finite state and action spaces is considered and an approach for determining the optimal pure and mixed stationary strategies for this problem is proposed. We show that the considered problem can be formulated in terms of stationary strategies where the objective function is quasi-monotonic (i. e. it is quasi-convex and quasi-concave) on the feasible set of stationary strategies. Using such a quasi-monotonic programming model with linear constraints we ground algorithms for determining the optimal pure and mixed stationary strategies for the average Markov decision problem.</p></cfAbstr> <cfResPubl_Class> <cfClassId>eda2d9e9-34c5-11e1-b86c-0800200c9a66</cfClassId> <cfClassSchemeId>759af938-34ae-11e1-b86c-0800200c9a66</cfClassSchemeId> <cfStartDate>2018-07-01T24:00:00</cfStartDate> </cfResPubl_Class> <cfResPubl_Class> <cfClassId>e601872f-4b7e-4d88-929f-7df027b226c9</cfClassId> <cfClassSchemeId>40e90e2f-446d-460a-98e5-5dce57550c48</cfClassSchemeId> <cfStartDate>2018-07-01T24:00:00</cfStartDate> </cfResPubl_Class> <cfPers_ResPubl> <cfPersId>ibn-person-129</cfPersId> <cfClassId>49815870-1cfe-11e1-8bc2-0800200c9a66</cfClassId> <cfClassSchemeId>b7135ad0-1d00-11e1-8bc2-0800200c9a66</cfClassSchemeId> <cfStartDate>2018-07-01T24:00:00</cfStartDate> </cfPers_ResPubl> <cfPers_ResPubl> <cfPersId>ibn-person-14970</cfPersId> <cfClassId>49815870-1cfe-11e1-8bc2-0800200c9a66</cfClassId> <cfClassSchemeId>b7135ad0-1d00-11e1-8bc2-0800200c9a66</cfClassSchemeId> <cfStartDate>2018-07-01T24:00:00</cfStartDate> </cfPers_ResPubl> </cfResPubl> <cfPers> <cfPersId>ibn-Pers-129</cfPersId> <cfPersName_Pers> <cfPersNameId>ibn-PersName-129-3</cfPersNameId> <cfClassId>55f90543-d631-42eb-8d47-d8d9266cbb26</cfClassId> <cfClassSchemeId>7375609d-cfa6-45ce-a803-75de69abe21f</cfClassSchemeId> <cfStartDate>2018-07-01T24:00:00</cfStartDate> <cfFamilyNames>Lozovanu</cfFamilyNames> <cfFirstNames>Dmitrii</cfFirstNames> </cfPersName_Pers> </cfPers> <cfPers> <cfPersId>ibn-Pers-14970</cfPersId> <cfPersName_Pers> <cfPersNameId>ibn-PersName-14970-3</cfPersNameId> <cfClassId>55f90543-d631-42eb-8d47-d8d9266cbb26</cfClassId> <cfClassSchemeId>7375609d-cfa6-45ce-a803-75de69abe21f</cfClassSchemeId> <cfStartDate>2018-07-01T24:00:00</cfStartDate> <cfFamilyNames>Pickl</cfFamilyNames> <cfFirstNames>Stefan Wolfgang</cfFirstNames> </cfPersName_Pers> </cfPers> </CERIF>