Python Deep Learning Projects

Q-learning

Q-learning is a policy-based reinforcement learning technique where the goal of Q-learning is to learn an optimal policy that helps an agent decide what action to take under which circumstances of the environment. 

To implement Q-learning, you need to understand what a Q function is.

A Q function accepts a state and a corresponding action as input and yields the total expected reward. It can be expressed as Q(s, a). When at the s state, an optimal Q function indicates to the agent how good of a choice is picking an action, a.

For a single state, s, and an action, a, Q(s, a) can be expressed in terms of the Q value of the next state, s', given by using the following equation:

This is known as the Bellman equation. It tells us that ...