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Discover the latest advancements in RLlib 2.0 through this 28-minute conference talk from Anyscale. Explore major improvements including a new algorithm configuration method, revamped core algorithm logics using plain Python implementations, and restructured algorithm and policy implementations for easier extension and customization. Learn about a feature that consolidates user environment interactions, simplifying the restoration and serving of RLlib policies. Gain insights into the integration between RLlib and the Ray AIR ecosystem. Understand how these enhancements make RLlib more intuitive, extensible, and performant for various research and production use cases.
