Grid World Sarsa Lambda Ai Project 5

Summary

Machine learning demo in which an agent strives to learn the optimal policy for reaching a goal from any starting state in a 20 x 20 ... An implementation of the value iteration algorithm for a specific case of the Player learning how to dribble. Modifications: * No reward for walls, simply reset the actor when they collide. * Negative reward added that the actor actively ... This video tutorial has been taken from Hands - On Reinforcement Learning with Python. You can learn more and buy the full ... Two reinforcement-learning agents, Q-learning and This video explains Double Q-Learning and n-step Github: github.com/scranton01/CS4242- Robot agent playing for 10 episodes after learning from 3000 episodes. Also, optimal policies learned is shown for each state.