FINITE STAGE CONTINUOUS TIME MARKOV DECISION PROCESSES WITH AN INFINITE PLANNING HORIZON,

Abstract

The system considered may be in one of n states at any point in time; its probability law is a Markov process that depends on the policy (control) chosen. The return to the system over a given planning horizon is the integral over that horizon of a return rate that depends on both the policy and the sample path of the process. The objective is to find a policy that maximizes the expected discounted return as the planning horizon tends to infinity. The case where the discount factor goes to zero is also considered. In all cases it is shown that there is a stationary policy that is optimal, and an algorithm is given to obtain that policy. (Author)

Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1967
Accession Number
AD0659730

Entities

People

  • Bruce L. Miller

Organizations

  • RAND Corporation

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Integrals
  • Markov Processes
  • Mathematics
  • Probability
  • Stationary

Fields of Study

  • Mathematics

Readers

  • Mathematical Modeling and Probability Theory.