Reinforcement Learning Using Deep Learning

Train deep neural network agents using reinforcement learning

You can build policy and value function representations for reinforcement learning applications using deep neural networks. You can then train these networks using Reinforcement Learning Toolbox™ software. For more information, see What Is Reinforcement Learning? (Reinforcement Learning Toolbox) and Create Policy and Value Function Representations (Reinforcement Learning Toolbox), and Train Reinforcement Learning Agents (Reinforcement Learning Toolbox).


Create Simulink Environment and Train Agent

Train a controller using reinforcement learning with a plant modeled in Simulink® as the training environment.

Create Agent Using Deep Network Designer and Train Using Image Observations

Create a reinforcement learning agent using the Deep Network Designer app from the Deep Learning Toolbox™.

Train DDPG Agent to Swing Up and Balance Pendulum with Image Observation

Train a reinforcement learning agent using an image-based observation signal.

Train DQN Agent for Lane Keeping Assist Using Parallel Computing

Train a reinforcement learning agent for a lane keeping assist application.

Featured Examples