2nd Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM), Edmonton 2015

Basics of Computational Reinforcement Learning

author: Michael Littman, Department of Computer Science, Rutgers, The State University of New Jersey
published: July 28, 2015, recorded: June 2015, views: 23153

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Description

In machine learning, the problem of reinforcement learning is concerned with using experience gained through interacting with the world and evaluative feedback to improve a system’s ability to make behavioral decisions. This tutorial will introduce the fundamental concepts and vocabulary that underlie this field of study. It will also review recent advances in the theory and practice of reinforcement learning, including developments in fundamental technical areas such as generalization, planning, exploration and empirical methodology.

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Reviews and comments:

1 HW, December 1, 2016 at 10:29 a.m.:

The videos seem to break too frequently. It is almost impossible to stay focused (I have checked my internet speed, etc.: it is fine). I had the same experience with Silver's "Deep Reinforcement Learning" tutorial video (http://videolectures.net/rldm2015_sil...

2 Atif, October 19, 2020 at 9:37 a.m.:

Thank you for sharing this.

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4 Catherine Rogers, December 20, 2021 at 12:28 p.m.:

Thanks for sharing!

5 Bruce Wayne, October 12, 2023 at 1:26 p.m.:

I just finished watching 'Basics of Computational Reinforcement Learning,' and I'm incredibly impressed! The video provided a clear and concise introduction to the fundamentals of reinforcement learning, making it accessible even for beginners like myself. The explanations were easy to follow, and the examples helped me grasp the concepts better. I can't wait to dive deeper into this exciting field of AI and machine learning. Kudos to the creators for an excellent educational resource!

6 Bruce Wayne, October 12, 2023 at 1:27 p.m.:

Basics of Computational Reinforcement Learning is a fantastic introduction to this complex field! The clear explanations and practical examples make it easy to grasp the fundamentals. I appreciate the straightforward approach, and it's a great starting point for anyone interested in RL. Kudos to the creators for making this content accessible and engaging!
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