Implementing Deep Reinforcement Learning Models with Tensorflow + OpenAI Gym
📰 Lilian Weng's Blog
Implementing deep reinforcement learning models using Tensorflow and OpenAI Gym
Action Steps
- Choose a deep reinforcement learning algorithm to implement
- Set up the OpenAI Gym environment for simulation
- Implement the model using Tensorflow
- Train and test the model
- Evaluate and refine the model's performance
Who Needs to Know This
Machine learning engineers and researchers can benefit from this implementation to develop and test their own reinforcement learning models, while software engineers can learn how to integrate these models into larger systems.
Key Insight
💡 Deep reinforcement learning models can be effectively implemented using Tensorflow and OpenAI Gym for simulation and training
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🤖 Implement deep reinforcement learning models with Tensorflow + OpenAI Gym!
Key Takeaways
Implementing deep reinforcement learning models using Tensorflow and OpenAI Gym
Full Article
<!-- Let's see how to implement a number of classic deep reinforcement learning models in code. --> <p>The full implementation is available in <a href="https://github.com/lilianweng/deep-reinforcement-learning-gym">lilianweng/deep-reinforcement-learning-gym</a></p> <p>In the previous two posts, I have introduced the algorithms of many deep reinforcement learning models. Now it is the time to get our hands dirty and practice how to implement the models in the wild. The implementation is gonna be
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