Unverified50% confidenceFactExact time
The core mechanism of CoPE is that, on successful on-policy trajectories, it simultaneously supervises the policy backbone to generate subsequent multi-step action sequences and each action to be individually predicted from its preceding history.
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50%
Confidence
Long-term
Relevance
10/15/2026
First Seen
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Unverified策略梯度方法本质上是on-policy的，因为梯度估计中的期望是关于当前策略分布的71% similarUnverifiedCoPE maintains the conventional one-step-at-a-time action approach during inference, produces no additional computational overhead, and requires no additional models, separate pre-training, or ensemble inference.68% similarUnverifiedUnlike traditional model predictive control (MPC), locomotion policy models compress complex balance and gait planning into a network capable of real-time inference, making deployment and iteration easier.67% similarUnverifiedMPC (Model Predictive Control) originated in the field of chemical process control, and its core idea is to solve an optimization problem based on a physical model within each control cycle using a receding horizon mechanism.66% similarUnverifiedThe plan-then-execute pattern uses one reasoning step to produce a plan and then a separate execution step to follow it, which reduces model drift or self-contradiction on execution details.66% similar
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