Avalanche RL: an End-to-End Library for Continual Reinforcement Learning

Avalanche RL is a fork of ContinualAI’s Pytorch-based framework Avalanche with the goal of extending its capabilities to Continual Reinforcement Learning (CRL), bootstrapping from the work done on Super/Unsupervised Continual Learning.

It should support all environments sharing the gym.Env interface, handle stream of experiences, provide strategies for RL algorithms and enable fast prototyping through an extremely flexible and customizable API.

The core structure and design principles of Avalanche are to remain untouched to easen the learning curve for all continual learning practitioners, so we still work with the same modules you can find in avl:

• Benchmarks for managing data and stream of data.
• Training for model training making use of extensible strategies.
• Evaluation to evaluate

   

   

   

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