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Machine Learning: Reinforcement Learning – Udacity

Udacity
0-6 Month Online
Intermediate Contact Institute
Online Big Data
Online Self Paced 2143

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This Reinforcement Learning course will teach you the algorithms for designing self-learning agents like us!

Reinforcement Learning is the area of Machine Learning concerned with the actions that software agents ought to take in a particular environment in order to maximize rewards. You can apply Reinforcement Learning to robot control, chess, backgammon, checkers, and other activities that a software agent can learn. Reinforcement Learning uses behaviorist psychology in order to achieve reward maximization.

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In this course, you will gain an understanding of topics and methods in Reinforcement Learning, including Markov Decision Processes and Game Theory. You will gain experience implementing Reinforcement Learning techniques in a final project.

In the final project, we’ll bring back the 80’s and design a Pacman agent capable of eating all the food without getting eaten by monsters.

Course Contents

  • Lesson 1: Markov Decision Processes
  • Lesson 2: Reinforcement Learning
  • Lesson 3: Game Theory
  • Lesson 4: Game Theory, Continued

Projects

Use a familiar Grid world domain to train a Reinforcement Learning agent and then design an agent that can play Pac man!

Duration:

1 month

Assumes 6 Hour per week (Work at your own pace)

Fees: – INR 11,940/Month (assuming $ = INR 60)

Part Time/Full time:

Part Time

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  • Programming experience and basic familiarity with statistics and probability theory is required.

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  • Charles Isbell
  • Michael Littman
  • Pushkar Kolhe

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