Applied Reinforcement Learning VI: Deep Deterministic Policy Gradients (DDPG) for Continuous Control | by Javier Martínez Ojeda | Mar, 2023
Introduction and theoretical explanation of the DDPG algorithm, which has many applications in the field of continuous controlPhoto by Eyosias G on UnsplashThe DDPG algorithm, first presented at ICLR 2016 by Lillicarp et al. , was a significant breakthrough in terms of Deep Reinforcement Learning algorithms for continuous control, because of its improvement over DQN (which only works with discrete actions), and its very good results and ease of implementation (see ).As for the NAF algorithm presented in the previous…