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.

Requisites:
Prerequisite: STAT 325 and MLAS 350 or CC 315

Typically Offered
Fall

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Kansas State University

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MLAS 500 - Reinforcement Learning in Autonomous Systems