Welcome to Q-Learning

Ladies and gentlemen, things are about to get even more interesting than before. The next model we are about to tackle is at the heart of many AIs built today; robots, autonomous vehicles, and even AI players of video games. They all use Q-learning at the core of their model. Some of them even combine Q-learning with deep learning, making a highly advanced version of Q-learning called deep Q-learning, which we will cover in Chapter 9, Going Pro with Artificial Brains – Deep Q-Learning.

All of the AI fundamentals still apply to Q-learning, as follows:

1. Q-learning is a Reinforcement Learning model.
2. Q-learning works on the inputs (states) and outputs (actions) principle.
3. Q-learning works on a predefined environment, including the states (the inputs), the actions (the outputs), and the rewards.
4. Q-learning is modeled by a Markov decision process.
5. Q-learning uses a training mode, during which the parameters that are learned...