Partially Observable Reinforcement Learning

Partially Observable Reinforcement Learning

Explore partial observable reinforcement learning in this 29-minute lecture from the CS885 course at the University of Waterloo. Delve into topics such as Partial Observable Markov Decisions, Hidden Markov Models, and Deep Recurrent Q Networks. Learn about belief monitoring, recurrent neural networks, and their applications in speech recognition. Gain insights into Markovian processes and long short-term memory networks. Access accompanying slides on the course website for a comprehensive understanding of this advanced machine learning concept.