Foundations of Reinforcement Learning
Dr. Soper discusses the foundations of reinforcement learning, which is one of the primary focus areas in the broader realm of artificial intelligence and cognitive computing systems. Topics of discussion include what reinforcement learning is and the five principles of reinforcement learning-based AI: The input and output system, rewards, the environment, the Markov decision process, and training vs. inference modes.
Previous lesson (Python Fundamentals - Part 03): https://youtu.be/c33FzYFcWfg
Next lesson (Reinforcement Learning: Thompson Sampling & The Multi Armed Bandit Problem - Part 01): https://youtu.be/yQwJiFFIgjA
Dr. Soper discusses the foundations of reinforcement learning, which is one of the primary focus areas in the broader realm of artificial intelligence and cognitive computing systems. Topics of discussion include what reinforcement learning is and the five principles of reinforcement learning-based AI: The input and output system, rewards, the environment, the Markov decision process, and training vs. inference modes.
Previous lesson (Python Fundamentals – Part 03): https://youtu.be/c33FzYFcWfg
Next lesson (Reinforcement Learning: Thompson Sampling & The Multi Armed Bandit Problem – Part 01): https://youtu.be/yQwJiFFIgjA
