Adaptive Policies for Markov Renewal Programs

Abstract

The paper recasts a class of infinite-state, infinite-action Markov renewal programs with unknown parameters as one-state programs with actions corresponding to stationary policies in the original program. Under suitable conditions, an adaptive (nonstationary) optimal policy is found in the sense of maximizing long-run expected reward per unit time.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1971
Accession Number
AD0737320

Entities

People

  • Bennett L. Fox
  • John E. Rolph

Organizations

  • RAND Corporation

Tags

Communities of Interest

  • C4I
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Air Force
  • Gain
  • High Gain
  • Inventory
  • Inventory Control
  • Lepidoptera
  • Linear Programming
  • Logistics
  • Markov Processes
  • Probability
  • Random Variables
  • Sampling
  • Sequences
  • Stationary
  • Transitions
  • United States

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Mathematical Modeling and Probability Theory.