Getting started with Deep Reinforcement Learning
Reinforcement Learning is a hot topic in Artificial Intelligence (AI) at the moment with the most prominent example of AlphaGo Zero. It shifted the boundaries of what was believed to be possible with AI. In this talk, we will have a look into Reinforcement Learning and its implementation. Reinforcement Learning is a class of algorithms which trains an agent to act optimally in an environment. The most prominent example is AlphaGo Zero, where the agent is trained to place tokens on the board of Go in order to win the game. AlphaGo Zero has won against the world champion which was thought to be impossible at that time. This was enabled by combining Reinforcement Learning with Deep Neural Networks and is today known as Deep Reinforcement Learning. This has shifted the frontier of Artificial Intelligence and enabled multiple complex use cases, among them controlling the cooling devices in the server rooms by google. Applying Deep Reinforcement Learning saved them several million in power costs. In this talk, we will understand the basics of Deep Reinforcement Learning and implement a simple example. We will have a look at OpenAIs gym which is the defacto standard for Reinforcement Learning environments. This will enable the audience to implement both an environment and Reinforcement Learning agent on their own.
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Getting started with Deep Reinforcement Learning
- 1. 1 16th of May 2019 Nicolas Kuhaupt Research Data Scientist Nicolaskuhaupt@aol.com Getting Started With Reinforcement Learning J on the Beach / Getting Started With Reinforcement Learning / Nicolas Kuhaupt
- 2. 2 16th of May 2019 1. Introduction to Reinforcement Learning 2. OpenAI Gym 3. Ray RLlib 4. Further Resources J on the Beach / Getting Started With Reinforcement Learning / Nicolas Kuhaupt
- 3. 3 16th of May 2019 1. Introduction to Reinforcement Learning 2. OpenAI Gym 3. Ray RLlib 4. Further Resources J on the Beach / Getting Started With Reinforcement Learning / Nicolas Kuhaupt
- 4. Reinforcement Learning 4 16th of May 2019 Agent Environment Action at State st Reward rt J on the Beach / Getting Started With Reinforcement Learning / Nicolas Kuhaupt
- 5. Atari Games 5 16th of May 2019J on the Beach / Getting Started With Reinforcement Learning / Nicolas Kuhaupt
- 6. Deep Reinforcement Learning 6 16th of May 2019 Environment Action at State st Reward rt Agent J on the Beach / Getting Started With Reinforcement Learning / Nicolas Kuhaupt
- 7. Deep Reinforcement Learning with Deep Q Networks 7 16th of May 2019 Regression: Input Data Prediction of continuous variable Classification: Input Data Score for Input being class A Score for Input being class B Reinforcement Learning: Estimated reward for action 1 Estimated reward for action 2 State J on the Beach / Getting Started With Reinforcement Learning / Nicolas Kuhaupt
- 8. Deep Q Networks 8 16th of May 2019J on the Beach / Getting Started With Reinforcement Learning / Nicolas Kuhaupt S0 S2 a0 a1 a2 a1 S1 a0 a2 0.3 1.0 0.7 0.2 0.8 1.0 1.0 0.10.1 0.8 40 10 50 Adapted from „Hands-On Machine Learning with Scikit-Learn & TensorFlow“ by Aurélien Géron
- 9. 9 16th of May 2019 1. Introduction to Reinforcement Learning 2. OpenAI Gym 3. Ray RLlib 4. Further Resources J on the Beach / Getting Started With Reinforcement Learning / Nicolas Kuhaupt
- 10. OpenAI Gym 10 16th of May 2019J on the Beach / Getting Started With Reinforcement Learning / Nicolas Kuhaupt https://gym.openai.com/envs/#mujoco
- 11. OpenAI Gym 11 16th of May 2019J on the Beach / Getting Started With Reinforcement Learning / Nicolas Kuhaupt https://gym.openai.com/envs/#robotics
- 12. Let´s Code 12 16th of May 2019J on the Beach / Getting Started With Reinforcement Learning / Nicolas Kuhaupt
- 13. 13 16th of May 2019 1. Introduction to Reinforcement Learning 2. OpenAI Gym 3. Ray RLlib 4. Further Resources J on the Beach / Getting Started With Reinforcement Learning / Nicolas Kuhaupt
- 14. Further Resources • Spinning up Reinforcement Learning from OpenAI (https://spinningup.openai.com/) • University Lectures (http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching.html) • Deep RL Bootcamp (https://sites.google.com/view/deep-rl-bootcamp/lectures) • Deepmind Blog (https://deepmind.com/blog/) 14 16th of May 2019J on the Beach / Getting Started With Reinforcement Learning / Nicolas Kuhaupt
- 15. 15 16th of May 2019 Nicolas Kuhaupt Research Data Scientist Nicolaskuhaupt@aol.com Thank you for your attention! J on the Beach / Getting Started With Reinforcement Learning / Nicolas Kuhaupt