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Explore the fundamentals of reinforcement learning in this lecture series delivered by Hugo Touchette from Stellenbosch University, South Africa at ICTS Bengaluru. Gain comprehensive insights into how agents make decisions in various environments while maximizing rewards. Master the theoretical foundations of reinforcement learning, including Markov decision processes and dynamical programming, along with essential learning methods such as temporal differences. Participate in two practical sessions that provide hands-on experience applying these concepts to real-world applications. The course spans eight lectures from November 1-25, 2024, with sessions held in the Emmy Noether Seminar Room, offering approximately 1.5-2 hours of instruction per lecture. Connect with the academic office for additional information and support throughout the learning journey.
A Short Course on Reinforcement Learning - Lecture 2