MA 617 - MARKOVIAN DECISION PROBLEMS

College of Arts & Sciences

Credits: 3

Control of discrete-time Markov processes by dynamic programming inventory theory. Computational approaches to control of Markov chains. State space methods: modeling of engineering and economic systems by linear stochastic difference equations. The discrete-time matrix Riccati equation, Kalman filtering. Optimal control of linear stochastic difference equations with complete or incomplete state information and with quadratic cost criterion.

Prerequisite(s):
Prereq: STA 624.