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Online Gain Tuning Using Neural Networks: A Comparative Study
This paper addresses the problem of adapting a control system to unseen conditions, specifically to the problem of trajectory tracking …
Ashley W.D. Hill, Jean Laneurit, Roland Lenain, Eric Lucet
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Online Gain Tuning Using Neural Networks: A Comparative Study
Online Tuning of Control Parameters for Off-Road Mobile Robots: Novel Deterministic and Neural Network-Based Approaches
This paper addresses the problem of the on-line adaptation of control parameters, dedicated to a path tracking problem in off-road …
Ashley W.D. Hill, Jean Laneurit, Roland Lenain, Eric Lucet
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A Novel Gradient Feature Importance Method for Neural Networks: An Application to Controller Gain Tuning for Mobile Robots
In the paper, a novel gradient-based feature importance method for neural networks is described. This method is compared to the …
Ashley W.D. Hill, Eric Lucet, Roland Lenain
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Stable-baselines3: Reliable reinforcement learning implementations
Stable-Baselines3 provides open-source implementations of deep reinforcement learning (RL) algorithms in Python. The implementations …
Antonin Raffin, Ashley W.D. Hill, Adam Gleave, Anssi Kanervisto, Maximilian Ernestus, Noah Dormann
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Stable-baselines3: Reliable reinforcement learning implementations