GAE Processing for Agent Trajectories
ziv_ravid · x · 2026-07-11
The author discusses how advantages are propagated in agent trajectories: model actions and environmental observations interleave. If standard GAE is applied directly, the advantage would propagate across many observation tokens that the model didn't actually "generate." To fix this, they connect the last token of an action directly to the first token of the next action, preventing learning signals from reaching places they shouldn't.
This is a typical discussion on agent training methods, focusing on how to process interaction trajectories more reasonably.
Related event: GLM Team Proposes SAO Algorithm for Asynchronous Agent RL(15 posts)→
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