Deep Reinforcement Learning with Python: With PyTorch, TensorFlow and OpenAI Gym

© Nimish Sanghi 2021

N. SanghiDeep Reinforcement Learning with Pythonhttps://doi.org/10.1007/978-1-4842-6809-4_6

6. Deep Q-Learning

Nimish Sanghi¹  

(1)

Bangalore, India

 

In this chapter, we will do a deep dive into Q-learning combined with function approximation using neural networks. Q-learning in the context of deep learning using neural networks is also known as Deep Q Networks (DQN) . We will first summarize what we have talked about so far with respect to Q-learning. We will then look at code implementations of DQN on simple problems followed by training an agent to play Atari games. Following this, we will extend our knowledge by looking at various modifications that can be done to DQN to improve the learning, including some very recent and ...