Machine Learning

Reinforcement learning has gained valuable popularity with the relatively recent success of DeepMind's AlphaGo method to beat the world champion Go player. The AlphaGo method was educated in part by reinforcement learning on deep neural networks. This style of learning is a distinct feature of machine learning from the classical supervised and unsupervised paradigms. In reinforcement learning, the network responds to environmental data (called the state) using deep neural networks and influences the behavior of an agent to try to optimize a reward. This technique helps a network to learn how to play sports, such as Atari or other video games, or some other challenge that can be rewritten as a form of the game. In this tutorial, a common model of reinforcement learning, I will introduce the broad principles of Q learning, and I will demonstrate how to incorporate deep Q learning in TensorFlow. Introduction to reinforcement learning As mentioned above, reinforcement learning consis