PPO
#CellStratAILab #disrupt4.0 #WeCreateAISuperstars #AlwaysUpskilling Reinforcement Learning (RL) refers to training agents with help of incentive-driven environments. RL typically involves a tuple of <state, action, reward> paradigm, which means that the agent has action choices to make in various states, and each action entails a potential reward. This also means that each state has a “value” […]
#CellStratAILab #disrupt4.0 #WeCreateAISuperstars #AlwaysUpskilling Minutes from Saturday 7th March 2020 AI Lab meetup at BLR :- Last Saturday, we had excellent sessions in the AI Lab meetup. Face Recognition with MTCNN and FaceNet :- First Amit Kumar presented a detailed overview of Face Recognition with MTCNN and FaceNet. Face Recognition involves a pipeline of Face […]
In my previous post, we discussed the simplest Policy Gradient REINFORCE. We saw, how Policy based methods are better than value based methods, a derivation of the Gradient of Score(Cost) function, and an implementation of simple Policy Gradient to train Gym’s Acrobot-v0. We then saw, how introducing a baseline reduces variance which leads to the […]