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Hi, sorry to bother you
I’m exploring how to implement Hierarchical Reinforcement Learning (HRL) within the Tianshou framework for a project involving multi-level decision-making tasks. Probably the exact same question as #805
I’d appreciate guidance on extending it for hierarchical setups.
Specifically for :
- How can I structure high-level policies and low-level policies within Tianshou’s Policy class?
- What is the recommended way to handle high-level and low-level policies ?
- How should hierarchical interactions be managed in the Collector and Trainer classes?
- Is there support for multi-phase sampling (e.g., high-level decisions feeding into low-level transitions)?
- Are there limitations in Tianshou’s current design that I should be aware of for HRL?
Thank you for your time, and I would greatly appreciate your response.
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