6 citations · 13 across the 4 of their papers we have counts for
5 papers · 1 filter
Modulation-Enhanced Excitation for Continuous-Time Reinforcement Learning via Symmetric Kronecker Products
Brent A. Wallace, Jennie Si
This work introduces new results in continuous-time reinforcement learning (CT-RL) control of affine nonlinear systems to address a major algorithmic challenge due to a lack of per…
Continuous-Time Reinforcement Learning: New Design Algorithms with Theoretical Insights and Performance Guarantees
Brent A. Wallace, Jennie Si
Continuous-time nonlinear optimal control problems hold great promise in real-world applications. After decades of development, reinforcement learning (RL) has achieved some of the…
Toward Reliable Designs of Data-Driven Reinforcement Learning Tracking Control for Euler-Lagrange Systems
Zhikai Yao, Jennie Si, Ruofan Wu +1
This paper addresses reinforcement learning based, direct signal tracking control with an objective of developing mathematically suitable and practically useful design approaches.…
Online Reinforcement Learning Control by Direct Heuristic Dynamic Programming: from Time-Driven to Event-Driven
Qingtao Zhao, Jennie Si, Jian Sun
In this paper time-driven learning refers to the machine learning method that updates parameters in a prediction model continuously as new data arrives. Among existing approximate…
Reinforcement Learning Control of Robotic Knee with Human in the Loop by Flexible Policy Iteration
Xiang Gao, Jennie Si, Yue Wen +3
We are motivated by the real challenges presented in a human-robot system to develop new designs that are efficient at data level and with performance guarantees such as stability…