FINITE STATE CONTINUOUS TIME MARKOV DECISION PROCESSES WITH A FINITE PLANNING HORIZON.

Abstract

The system considered may be in one of n states at any point in time and its probability law is a Markov process which 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 which depends on both the policy and the sample path of the process. The objective is to find a policy which maximizes the expected return over the given planning horizon. A necessary and sufficient condition for optimality is obtained, and a constructive proof is given that there is a piecewise constant policy which is optimal. A bound on the number of switches (points where the piecewise constant policy jumps) is obtained for the case where there are two states. (Author)

Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1967
Accession Number
AD0651467

Entities

People

  • Bruce L. Miller

Organizations

  • RAND Corporation

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Integrals
  • Markov Processes
  • Mathematics
  • Probability

Fields of Study

  • Mathematics

Readers

  • Calculus or Mathematical Analysis
  • Operations Research