ECE 586

Fall 2025 Part of Term 1

Part of Term 1
Aug 25-Dec 10

Credit: 4 hours.

Lectures and discussions related to advanced topics and new areas of interest in decision and control theory: hybrid, sampled-data, and fault tolerant systems; control over networks; vision-based control; system estimation and identification; dynamic games.

May be repeated up to 12 hours within a term, and up to 20 hours total for the course. Credit towards a degree from multiple offerings of this course is not given if those offerings have significant overlap, as determined by the ECE department. Prerequisite: As specified each term. It is expected that each offering will have a 500-level course as prerequisite or co-requisite.

ECE 586 class schedule data for fall 2025
CRN Type Section Time Day Location Instructor Section Details
51292
Lecture
RS
12:30PM -1:50PM
TR
106B8 Engineering Hall
Srikant, R
Part of Term:
1
Date Range:
08/25/25-12/10/25
Credit:
4 hours
Section Title:
MDPs, Reinforcement Learning
Section Info:
Topic: MDPs, Reinforcement Learning. Prerequisites: ECE 534. The course will discuss techniques to solve dynamic optimization problems where the system dynamics are unknown. The course will first introduce dynamic programming techniques for Markov decision problems and then focus on solving the dynamic programming equations approximately when the underlying parameters of the Markov chain are unknown. While the emphasis will be on techniques for which one can prove performance bounds, heuristics used in reinforcement learning will also be presented to show their relationship to existing theory, and to identify open theoretical problems.
Restriction(s):
Restricted to Graduate - Urbana-Champaign.
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