Lyapunov Exponent as Physics-Informed Dense Reward: RL Discovery of Stabilization Beyond the Kapitza Pendulum
Abstract
We suggest using the Lyapunov characteristic exponent (LCE) as a dense reward signal for the reinforcement learning problem of stabilizing the inverted pendulum with vertical motion. With LCE, the agent not only successfully found the oscillatory motion known as the Kapitza pendulum but also damped the pendulum's pivoting, leaving it in a strictly upright position. --- Source: arXiv:2607.14001v1 - http://arxiv.org/abs/2607.14001v1 PDF: https://arxiv.org/pdf/2607.14001v1 Original Link: http://arx...
Description / Details
We suggest using the Lyapunov characteristic exponent (LCE) as a dense reward signal for the reinforcement learning problem of stabilizing the inverted pendulum with vertical motion. With LCE, the agent not only successfully found the oscillatory motion known as the Kapitza pendulum but also damped the pendulum's pivoting, leaving it in a strictly upright position.
Source: arXiv:2607.14001v1 - http://arxiv.org/abs/2607.14001v1 PDF: https://arxiv.org/pdf/2607.14001v1 Original Link: http://arxiv.org/abs/2607.14001v1
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Jul 16, 2026
Data Science
Machine Learning
0