Deep Reinforcement Learning in Action

List of Listings

Chapter 2. Modeling reinforcement learning problems: Markov decision processes

Listing 2.1. Finding the best actions given the expected rewards in Python 3

Listing 2.2. Epsilon-greedy strategy for action selection

Listing 2.3. Defining the reward function

Listing 2.4. Updating the reward record

Listing 2.5. Computing the best action

Listing 2.6. Solving the n-armed bandit

Listing 2.7. The softmax function

Listing 2.8. Softmax action-selection for the n-armed bandit

Listing 2.9. Contextual bandit environment

Listing 2.10. The main training loop

Chapter 3. Predicting the best states and actions: Deep Q-networks

Listing 3.1. Creating a Gridworld game

Listing 3.2. Neural network Q function

Listing 3.3. Q-learning: Main training ...