CONTROLS LEADING TO OPTIMAL STATIONARY REGIMES,

Abstract

The authors define a controlled Markov chain as one for which the passage probabilities are defined by P(xi sub (n + 1) = X sub (n + 1) (vertical line) xi sub n, d sub n); n = 0,1,... where d sub n is an element which may be chosen from a space D as a function of x sub 0,...,x sub n. A choice of d sub n(x sub 0,...,x sub n) for each n = or > 0 is called a control delta; and it is noted that the process (xi, delta), xi = (xi sub 1, xi sub 2,...), delta = (d sub 1, d sub 2,...) is generally not really Markovian (since the further past has too much influence). The control delta is called Markovian if each of the functions d sub n depends only on x sub n, and homogeneous Markovian if in addition, all d sub n are the same. The authors define admissible controls; they define optimal controls in terms of a loss function W(x, d) where x is the state of the system and d the chosen control. They answer the question of existence of optimal controls and optimal homogeneous Markov controls for the very special case of finite state and control spaces.

Document Details

Document Type
Technical Report
Publication Date
Sep 19, 1967
Accession Number
AD0666741

Entities

People

  • A. N. Shiryaev
  • O. V. Viskov

Organizations

  • National Air and Space Intelligence Center

Tags

DTIC Thesaurus Topics

  • Markov Chains
  • Markov Processes
  • Mathematics
  • Probability
  • Stationary

Readers

  • Analytical Mechanics
  • Mathematical Modeling and Probability Theory.
  • Robotics and Automation.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms
  • Space
  • Space - Orbital Debris
  • Space - Spacecraft Maneuvers