Hands-On Reinforcement Learning with Python

Solving the taxi problem using Q learning

To demonstrate the problem let's say our agent is the driver. There are four locations and the agent has to pick up a passenger at one location and drop them off at another. The agent will receive +20 points as a reward for successful drop off and -1 point for every time step it takes. The agent will also lose -10 points for illegal pickups and drops. So the goal of our agent is to learn to pick up and drop off passengers at the correct location in a short time without adding illegal passengers.

The environment is shown here, where the letters (R, G, Y, B) represent the different locations and a tiny rectangle is the agent driving the taxi:

Let's look at the coding part:

import gymimport random ...