mohmdelsayed/streaming-drl
Deep reinforcement learning without experience replay, target networks, or batch updates.
This project offers robust algorithms for training intelligent agents that learn continuously from real-time data streams without needing to store past experiences. It takes in live observations and rewards, producing an agent that makes immediate, improved decisions. This is ideal for machine learning engineers, robotics developers, or control systems designers working with dynamic environments and limited memory resources.
279 stars. No commits in the last 6 months.
Use this if you need to train deep reinforcement learning agents that can adapt quickly to changes in real-time environments using continuous streams of data, particularly when memory or privacy constraints prevent storing large amounts of experience.
Not ideal if your application allows for offline training with batch updates and experience replay, or if computational resources are not a primary constraint.
Stars
279
Forks
33
Language
Python
License
—
Category
Last pushed
Mar 18, 2025
Commits (30d)
0
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