主动推理和功能参数化:差异平度和平滑随机实现
Hugues Mounier1, Thomas Parr2, Karl Friston3,4
1Laboratoire des Signaux et Systèmes, Université Paris-Saclay, Centre National de la Recherche Scientifique, CentraleSupélec, 3, rue Joliot Curie, 91192 Gif sur Yvette, France.
Entropy (Basel, Switzerland)
|January 28, 2026
概括
这项研究将非线性控制理论与主动推理联系起来,探索用于设计生成模型的差异平面性. 这种方法使用系统导数和通用坐标来控制应用程序,用眼运动控制来证明.
科学领域:
- 机器人和控制系统 机器人和控制系统
- 计算神经科学是一种神经科学.
- 机器学习 机器学习
背景情况:
- 积极推断模型使用生成模型做决策.
- 建设性的非线性控制理论提供了系统的设计方法.
- 跨越这些领域对于先进的自主系统至关重要.
研究的目的:
- 探索微分平面度与主动推理生成模型之间的联系.
- 调查差异平面系统的路径属性如何影响控制设计.
- 作为一个案例研究,将这些概念应用于眼运动控制.
主要方法:
- 使用一般化坐标制定连续时间生成模型.
- 分析由差异平面系统的时间导数得出的路径属性.
- 在主动推理框架内整合构造性的非线性控制技术.
主要成果:
- 展示了一个结合控制理论和主动推理的新框架.
- 突出了差异平坦度在设计控制的生成模型中的实用性.
- 使用眼运动控制动力学提供了一个概念插图.
结论:
- 微分平面性为设计强大的主动推理控制器提供了一个有希望的途径.
- 整合促进了更复杂的自主系统的开发.
- 进一步的研究可以将这个框架扩展到更复杂的控制问题.
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