Representation over Routing: Diagnosing Temporal Routing Pathologies in Multi-Timescale PPO
Temporal credit assignment in reinforcement learning is often approached by introducing value estimates at multiple discount factors. A natural next step is to let the actor dynamically route among these temporal heads, using either differentiable attention or heuristic uncertainty weights. This paper argues that such routing can create a numerical shortcut rather than a reliable temporal abstraction. We study this issue in a controlled PPO setting on LunarLander-v2, using the environment as a visual sandbox for diagnosing failure modes. First, we formalize Surrogate Objective Hacking: a differentiable softmax router exposed to the PPO surrogate receives a direct gradient toward advantage...
| Authors | Jing Sun |
|---|---|
| Primary category | cs.LG |
| Published | 15 April 2026 |
| Last updated at source | 30 May 2026 |
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