paper_rl__qc
CommunityChunk actions for long-horizon TD-RL.
Education & Research#reinforcement-learning#rl#action-chunking#offline-to-online#n-step-returns#jax-flax
AuthorGonglitian
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Action chunking enables TD-based RL to operate with temporally extended decisions.
Core Features & Use Cases
- Action chunking supports long-horizon decision making in offline-to-online RL.
- Two agent variants (ACFQL and ACRLPD) with n-step bootstrapping for stable learning.
- Integrates with main.py and main_online.py for offline-to-online and online-only workflows.
Quick Start
Run offline-to-online experiments with a best-of-N or distill-DDPG actor on a long-horizon task.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
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Please help me install this Skill: Name: paper_rl__qc Download link: https://github.com/Gonglitian/agent-skills/archive/main.zip#paper-rl-qc Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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