Risk-Aware Control
Risk-Aware Control
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DOI：
10.1162/neco_a_00662
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发表时间：
2014-12-01
影响因子：
2.9
通讯作者：
Sanger, Terence D.
中科院分区：
文献类型：
--
作者：
Sanger, Terence D.
人类运动不同于机器人控制，因为它在未知环境中具有灵活性、对扰动的鲁棒性以及对未知参数和不可预测的变化的容忍度。我们提出了一种新的理论，即风险意识控制，其中运动是由基于当前状态的不确定性和错误成本的知识的风险估计来控制的。我们证明了实现风险感知控制的反馈控制律的存在，并表明该控制律可以由尖峰神经元群体直接实现。提供了时变成本函数的风险感知控制以及随机风险环境中未知动态学习的模拟示例。
Human movement differs from robot control because of its flexibility in unknown environments, robustness to perturbation, and tolerance of unknown parameters and unpredictable variability. We propose a new theory, risk-aware control, in which movement is governed by estimates of risk based on uncertainty about the current state and knowledge of the cost of errors. We demonstrate the existence of a feedback control law that implements risk-aware control and show that this control law can be directly implemented by populations of spiking neurons. Simulated examples of risk-aware control for time-varying cost functions as well as learning of unknown dynamics in a stochastic risky environment are provided.