Ashley Hill | hill-a
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Reinforcement Learning
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 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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Online velocity fluctuation of off-road wheeled mobile robots: A reinforcement learning approach
During the off-road path following of a wheeled mobile robot in presence of poor grip conditions, the longitudinal velocity should be …
François Gauthier-Clerc
,
Ashley W.D. Hill
,
Jean Laneurit
,
Roland Lenain
,
Eric Lucet
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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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Online gain setting method for path tracking using CMA-ES: Application to off-road mobile robot control
This paper proposes a new approach for online control law gains adaptation, through the use of neural networks and the Covariance …
Ashley W.D. Hill
,
Jean Laneurit
,
Roland Lenain
,
Eric Lucet
PDF
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CES-IA Reinforcement Learning Class
The CES-IA Reinforcement learning class slides.
Apr 4, 2020 9:00 AM
Paris, France
Ashley W.D. Hill
Slides
RL Tutorial on Stable Baselines
Beginner tutorial on Stable Baselines library with colab notebooks
Oct 18, 2019 9:00 AM
Vittel, France
Antonin Raffin
,
Edward Beeching
,
Ashley W.D. Hill
Code
Project
ICINCO presentation
The presentation of the 2019 ICINCO paper
Jul 29, 2019 12:00 PM
Prague, Czech Republic
Ashley W.D. Hill
Slides
Neuroevolution with CMA-ES for real-time gain tuning of a car-like robot controller
This paper proposes a method for dynamically varying the gains of a mobile robot controller that takes into account, not only errors to …
Ashley W.D. Hill
,
Eric Lucet
,
Roland Lenain
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Slides
Video
Decoupling feature extraction from policy learning: assessing benefits of state representation learning in goal based robotics
Scaling end-to-end reinforcement learning to control real robots from vision presents a series of challenges, in particular in terms of …
Antonin Raffin
,
Ashley W.D. Hill
,
René Traoré
,
Timothée Lesort
,
Natalia Díaz-Rodríguez
,
David Filliat
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