CoPE boosts agent RL sample efficiency via multi-step action forecasting
Haofei Yu · hf · 2026-10-20
CoPE improves agentic reinforcement learning by training policies to generate multi-step action sequences from trajectory histories, increasing sample efficiency without adding inference overhead.
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