We finally kicked off our MLT Reinforcement Learning sessions with an "Intro to RL" study group at the Tokyo Metropolitan Library. Anugraha Sinha walked us through the following: Theory Introduction to RL Important elements of an RL problem Description of Markov Decision Process (MDP) and and Markov Assumption. Importance of parametrization of State, Action, Reward … Continue reading INTRO TO REINFORCEMENT LEARNING