How to train your robot (with Deep Reinforcement Learning) by Lucas García
Channel: Big Things Conference
Date: 04/12/2019

The talk addresses the full workflow for Deep Reinforcement Learning: choosing an adequate environment, crafting a reward function, choosing a policy function, training and deployment. Using Model-Based Design, the talk demonstrates how to build and control a virtual biped humanoid robot in Simulink and leverages Deep Reinforcement Learning in MATLAB, specifically the Deep Deterministic Policy Gradient (DDPG), to successfully train the agent. Finally, we discuss how to deploy the optimal policies to the target hardware, using C/C++ or CUDA.

#BIGTH19 #AI #DeepLearning

Session presented at Big Things Conference 2019 by Lucas García, Senior Application Engineer at MathWorks.

20th November 2019
Kinépolis, Madrid

Do you want to know more? https://www.bigthingsconference.com/