Search Results for author: John Valasek

Found 5 papers, 1 papers with code

Gaze-Informed Multi-Objective Imitation Learning from Human Demonstrations

no code implementations25 Feb 2021 Ritwik Bera, Vinicius G. Goecks, Gregory M. Gremillion, Vernon J. Lawhern, John Valasek, Nicholas R. Waytowich

In the field of human-robot interaction, teaching learning agents from human demonstrations via supervised learning has been widely studied and successfully applied to multiple domains such as self-driving cars and robot manipulation.

Imitation Learning Navigate +2

Combining Visible and Infrared Spectrum Imagery using Machine Learning for Small Unmanned Aerial System Detection

no code implementations27 Mar 2020 Vinicius G. Goecks, Grayson Woods, John Valasek

However, compared to widely available visible spectrum sensors, LWIR sensors have lower resolution and may produce more false positives when exposed to birds or other heat sources.

BIG-bench Machine Learning object-detection +1

PODNet: A Neural Network for Discovery of Plannable Options

no code implementations1 Nov 2019 Ritwik Bera, Vinicius G. Goecks, Gregory M. Gremillion, John Valasek, Nicholas R. Waytowich

Learning from demonstration has been widely studied in machine learning but becomes challenging when the demonstrated trajectories are unstructured and follow different objectives.

Integrating Behavior Cloning and Reinforcement Learning for Improved Performance in Dense and Sparse Reward Environments

no code implementations9 Oct 2019 Vinicius G. Goecks, Gregory M. Gremillion, Vernon J. Lawhern, John Valasek, Nicholas R. Waytowich

However, it is currently unclear how to efficiently update that policy using reinforcement learning as these approaches are inherently optimizing different objective functions.

Q-Learning reinforcement-learning

Efficiently Combining Human Demonstrations and Interventions for Safe Training of Autonomous Systems in Real-Time

1 code implementation26 Oct 2018 Vinicius G. Goecks, Gregory M. Gremillion, Vernon J. Lawhern, John Valasek, Nicholas R. Waytowich

This paper investigates how to utilize different forms of human interaction to safely train autonomous systems in real-time by learning from both human demonstrations and interventions.

Imitation Learning

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