2025-2026 Undergraduate Catalog
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AAAI 490 - AICE: Introduction to Reinforcement Learning When Offered: F, S, SS
3 Credit(s) 3 Lecture Hour(s) 0 Lab Hour(s)
This course aims to provide students with a comprehensive understanding of reinforcement learning (RL) principles and practical skills in implementing RL algorithms. Students will learn to develop and apply RL solutions using state-of-the-art tools and frameworks. The course will cover fundamental concepts, value-based and policy-based methods, and their applications in various engineering domains. By the end of the course, students will be equipped to design, implement, and evaluate RL systems for complex decision-making problems.
Prerequisite(s): TBA - Some Deep Learning Course/ Probability Course/Programming Corequisite(s): none
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