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→Active inference 主动推理
When gradient descent is applied to action <math> \dot{a} = -\partial_aF(s,\tilde{\mu}) </math>, motor control can be understood in terms of classical reflex arcs that are engaged by descending (corticospinal) predictions. This provides a formalism that generalizes the equilibrium point solution – to the [[degrees of freedom problem]]<ref>Feldman, A. G., & Levin, M. F. (1995). [http://e.guigon.free.fr/rsc/article/FeldmanLevin95.pdf The origin and use of positional frames of reference in motor control]. Behav Brain Sci. , 18, 723–806.</ref> – to movement trajectories.
When gradient descent is applied to action <math> \dot{a} = -\partial_aF(s,\tilde{\mu}) </math>, motor control can be understood in terms of classical reflex arcs that are engaged by descending (corticospinal) predictions. This provides a formalism that generalizes the equilibrium point solution – to the [[degrees of freedom problem]]<ref>Feldman, A. G., & Levin, M. F. (1995). [http://e.guigon.free.fr/rsc/article/FeldmanLevin95.pdf The origin and use of positional frames of reference in motor control]. Behav Brain Sci. , 18, 723–806.</ref> – to movement trajectories.
当梯度下降应用于动作<math>\dot{a}=-\partial\u aF（s，\tilde{\mu}）</math>时，运动控制可以理解为通过下降（皮质脊髓）预测参与的经典反射弧。这提供了一种形式主义，将平衡点解推广到[[自由度问题]]<ref>Feldman, A. G., & Levin, M. F. (1995). [http://e.guigon.free.fr/rsc/article/FeldmanLevin95.pdf The origin and use of positional frames of reference in motor control]. Behav Brain Sci. , 18, 723–806.</ref>移动轨迹。
=== Active inference and optimal control 主动推理与最优控制===
=== Active inference and optimal control 主动推理与最优控制===