Hands-On Reinforcement Learning for Games

Coding a value learner

Since this is our first example, make sure your Python environment is set to go. Again for simplicity, we prefer Anaconda. Make sure you are comfortable coding with your chosen IDE and open up the code example, Chapter_1_1.py, and follow along:

1. Let's examine the first section of the code, as shown here:

import randomreward = [1.0, 0.5, 0.2, 0.5, 0.6, 0.1, -.5]arms = len(reward)episodes = 100learning_rate = .1Value = [0.0] * armsprint(Value)

2. We first start by doing import of random. We will use random to randomly select an arm during each training episode.
3. Next, we define a list of rewards, reward. This list defines the reward for each arm (action) and hence defines the number of arms/actions on the bandit.
4. Then, ...