Preprint Open access
Targeting Pivotal Decisions for Credit Assignment in Agentic Reinforcement Learning
Group Relative Policy Optimization (GRPO) has become a promising approach for training large language model agents. However, its uniform assignment of trajectory-level advantages to all policy tokens fails to distinguish consequential decisions from less relevant ones, obscuring which intermediate decisions contributed …