Accession Number:

AD0652797

Title:

NON-DISCOUNTED DENUMERABLE MARKOVIAN DECISION MODELS

Descriptive Note:

Technical rept.

Corporate Author:

STANFORD UNIV CA DEPT OF STATISTICS

Personal Author(s):

• Ross, Sheldon M.

Report Date:

1967-05-02

Pagination or Media Count:

39.0

Abstract:

Countable state, finite action Markovian decision processes are studied under the average cost criterion. The problem is studied by using the known results for the discounted-cost problem. Sufficient conditions are given for the existence of an optimal rule which is of the stationary deterministic type. This rule is shown to be, in some sense, a limit point of the optimal discounted-cost rules. Sufficient conditions are also given for the optimal discounted-cost rules to be epsilon-optimal with respect to the average cost criterion. It is shown that if there is a replacement action then there exists an optimal rule but it may not be of the stationary deterministic type. It is also shown how, in a special case, the average cost criterion can be reduced to the discounted cost criterion. Lastly, an example is given of a process for which there exists an optimal nonstationary rule which is better than any stationary rule.

Descriptors:

• *DECISION THEORY
• *PROBABILITY
• DYNAMIC PROGRAMMING
• OPERATIONS RESEARCH
• OPTIMIZATION
• REPLACEMENT THEORY
• SEQUENCES(MATHEMATICS)
• STATISTICAL PROCESSES
• THEOREMS

Subject Categories:

• Operations Research

Distribution Statement:

APPROVED FOR PUBLIC RELEASE