Accession Number:

AD0724753

Title:

Markov Decision Processes with a New Optimality Criterion.

Descriptive Note:

Technical rept.,

Corporate Author:

STANFORD UNIV CALIF DEPT OF OPERATIONS RESEARCH

Personal Author(s):

Report Date:

1971-05-01

Pagination or Media Count:

108.0

Abstract:

A Markov decision process can be characterized by specifying the following three elements a Markov process on which a return function and decision structure is placed, an objective function or optimality criterion, and a class of allowable policies or controls. For a given Markov decision process with these three elements suitably defined, the standard problems to investigate are the following The existence of a policy, within the class of allowable policies, which attains the maximal value of the objective function The fact that the optimal policy has a simple form The construction of a finite algorithm to compute the optimal policy. The report discusses these problems for standard Markov decision processes with a new optimality criterion. Author

Subject Categories:

  • Operations Research

Distribution Statement:

APPROVED FOR PUBLIC RELEASE