MLAS 500 - Reinforcement Learning in Autonomous Systems

Credits: 3

This course will guide students through the development and operationalization of reinforcement learning frameworks. Reinforcement learning architectures such as Markov decision processes, Q-Learning, artificial neural networks, recurrent neural networks, and generative adversarial networks will be explored. This course is a guide to the complexities of reinforcement learning, their respective architectures and implementations within an autonomous system.

Repeat for Credit
N

Requisites
Prerequisite: STAT 225 and MLAS 350 or CC 315

Typically Offered
Fall

K-State 8
Empirical and Quantitative Reasoning

Kansas State University

Course Catalog

MLAS 500 - Reinforcement Learning in Autonomous Systems