CPSI46013 — Reinforcement Learning
Add to Bookmarks Three hours lecture. Three credit hours. Provides a comprehensive introduction to reinforcement learning (RL), the area of machine learning concerned with agents that learn to make sequential decisions through interaction with an environment. Students will explore foundational concepts, including Markov Decision Processes, dynamic programming, and temporal difference learning, before progressing to advanced topics such as deep reinforcement learning, policy search methods, and multi-agent systems. The course emphasizes both theoretical understanding and practical implementation, with hands-on programming exercises using modern RL frameworks. Prerequisites: CPSI 31303 - Machine Learning II
Prerequisites: CPSI31303