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Offered By: IBM

Monte Carlo Reinforcement Learning for Simple Games

Have you ever thought about training your own recommendation system or building your own robot or creating your own chess AI that can beat even the most experienced player? Reinforcement Learning is what you need. In this project, you will explore the basics of Reinforcement Learning and Monte Carlo Method. You will learn about training your own agent to navigate and succeed in simple and complex games/environments. Discover better ways to train your agent and how to work with the environment.

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Guided Project

Artificial Intelligence

503 Enrolled
4.4
(83 Reviews)

At a Glance

Have you ever thought about training your own recommendation system or building your own robot or creating your own chess AI that can beat even the most experienced player? Reinforcement Learning is what you need. In this project, you will explore the basics of Reinforcement Learning and Monte Carlo Method. You will learn about training your own agent to navigate and succeed in simple and complex games/environments. Discover better ways to train your agent and how to work with the environment.

Why you should do this Guided Project

Deep Blue a chess computer beat world chess champion Garry Kasparov in 1997. The game of Go is played on a 19 by 19 board and is much more difficult to play as there are about 10 to the power 360 different combinations. It was thought it would take decades before a computer beat a Go champion. But now, thanks to reinforcement learning, computers can easily beat Go champions, beat Chess Grandmasters and outperform Humans in every game. In this project, you will use Monte Carlo Reinforcement learning algorithms for the simple game Frozen lake. You will quickly grape import concepts of Reinforcement learning and apply open AI's  gym, the go-to framework for Reinforcement learning.

For example, the agent will be able to guide itself through a simple environment:

A Look at the Project Ahead

In this object you will learn how to:
  • Work with an OpenAI Gym environments
  • Explain what Reinforcement Learning is
  • Explain what Monte Carlo Method is
  • Create an agent that uses Monte Carlo Method to play Frozen Lake
  • Train and Test the agents using the Frozen Lake environment
  • Improve and update your algorithm.

What You'll Need

  • Knowledge of python programming language.

Frequently Asked Questions

  • Do I need to install any software to participate in this project?
    Everything you need to complete this project will be provided to you via the Skills Network Labs and it will all be available via a standard web browser.



  • What web browser should I use?
    The Skills Network Labs platform works best with current versions of Chrome, Edge, Firefox, Internet Explorer, or Safari.

Level

Beginner

Skills You Will Learn

Artificial Intelligence, Machine Learning, Python

Language

English

Course Code

GPXX0MNFRU

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