What is RLLab?
RLLab is an open-source toolkit designed for Reinforcement Learning (RL). It serves as a powerful platform for users to effortlessly construct, train, and assess intricate RL models across various environments. With its user-friendly interface, RLLab enables users to swiftly embark on their projects. It encompasses a plethora of features and tools, including a diverse array of sample environments, an extensive library of RL algorithms, and the capability to seamlessly integrate with external libraries and tools. Moreover, RLLab offers a comprehensive set of visualization tools, aiding users in comprehending their RL models and analyzing results effectively. Whether you are a novice or an expert, RLLab caters to individuals interested in exploring RL. It facilitates quick experimentation, customization of models, and provides valuable insights into their performance. Embarking on RL with RLLab opens up a world of possibilities for enthusiasts and professionals alike.
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RLLab FQA
- How do I install RLLab?
- How do I run experiments with RLLab?
- How can I integrate RLLab with OpenAI Gym?
- Can I implement new environments with RLLab?
- Is there documentation available for implementing new algorithms in RLLab?
RLLab Use Cases
Installation
Running Experiments
Integrating with OpenAI Gym
Implementing New Environments
Implementing New Algorithms (Basic)
Implementing New Algorithms (Advanced)
Running jobs on EC2