Easy 21

Reinforcement learning agent for learning to play to a modified version of blackjack.

Algorithms

• Monte carlo,
• Sarsa(lambda),
• Sarsa(lambda) + Linear Approx

How to run the agent

In order to test the system and see some relevant metrics concerning its performance you can run the file "testing.py"

Structure

The code is structured in two main classes

• Agent: Implements a suitable reinforcement learning algorithm to learn to play blackjack from experience.

• Environment: Provides feedback to user's actions, by providing a state representation and a reward signal.