Watch Ai Learn To Walk Using Deep Reinforcement Learning (drl)

Deep Reinforcement Learning (DRL) is a subfield of machine learning that combines neural networks with reinforcement learning techniques to make decisions in complex environments. An experiment was conducted to observe an AI agent, Albert, learning to walk in order to escape from five different rooms. The AI’s actions are controlled by a neural network, which is updated after each attempt in order to increase rewards and decrease punishments. The agent is typically a simulated or physical robot with legs and the state space includes variables like leg positions, joint angles, and velocity.