Twin-World Credit Assignment for Agentic Reinforcement Learning
This study introduces twin-world credit assignment to address sampling noise and isolate decision effects in agentic reinforcement learning episodes.
This study introduces twin-world credit assignment to address sampling noise and isolate decision effects in agentic reinforcement learning episodes.