From the series: MATLAB Oil and Gas Conference 2019
Reinforcement learning allows you to solve control problems using deep learning without using labeled data. Instead, it uses a model of your system that captures the appropriate dynamics of the environment and learns through performing multiple simulations. This simulation data is used to train a policy which is often represented by a deep neural network that would then replace your traditional controller or decision-making system.
In this talk, you will learn how to use Reinforcement Learning Toolbox™ and other MathWorks products to set up your environment models, define the policy and its various hyperparameters, and scale training through parallel computing to improve performance.
Select a Web Site
Choose a web site to get translated content where available and see local events and offers. Based on your location, we recommend that you select: .Select web site
You can also select a web site from the following list:
Select the China site (in Chinese or English) for best site performance. Other MathWorks country sites are not optimized for visits from your location.