Kyle R. Williams

According to our database, Kyle R. Williams authored at least 8 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2024

Explainable AI and Robustness-Based Test and Evaluation of Reinforcement Learning.

Ali K. Raz, Kshitij Mall, Sean Matthew Nolan, Winston Levin, Linas Mockus, Kristopher L. Ezra, Ahmad Mia, Kyle R. Williams, Julie Parish

IEEE Trans. Aerosp. Electron. Syst., October, 2024

Leveraging Machine Learning for Generating and Utilizing Motion Primitives in Adversarial Environments.

Zachary C. Goddard, Rithesh Rajasekar, Madhumita Mocharla, Garrett Manaster, Kyle R. Williams, Anirban Mazumdar

J. Aerosp. Inf. Syst., 2024

Leveraging Machine Learning to Improve Adaptive Primitive-Based Motion Planning.

Kevin S. Choi, Zachary C. Goddard, Samuel J. Deal, Anirban Mazumdar, Kyle R. Williams

J. Aerosp. Inf. Syst., 2024

2023

Trajectory Planning With Deep Reinforcement Learning in High-Level Action Spaces.

Kyle R. Williams, Rachel Schlossman, Daniel Whitten, Joe Ingram, Srideep Musuvathy, James Pagan, Kyle A. Williams, Sam Green, Anirudh Patel, Anirban Mazumdar, Julie Parish

IEEE Trans. Aerosp. Electron. Syst., June, 2023

Selecting Minimal Motion Primitive Libraries with Genetic Algorithms.

Zachary C. Goddard, Kenneth Wardlaw, Kyle R. Williams, Anirban Mazumdar

J. Aerosp. Inf. Syst., 2023

2022

Utilizing Reinforcement Learning to Continuously Improve a Primitive-Based Motion Planner.

Zachary C. Goddard, Kenneth Wardlaw, Kyle R. Williams, Julie Parish, Anirban Mazumdar

J. Aerosp. Inf. Syst., July, 2022

2021

Dakota and Pyomo for Closed and Open Box Controller Gain Tuning.

Kyle R. Williams, J. Justin Wilbanks, Rachel Schlossman, David Kozlowski, Julie Parish

Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

2018

Real-Time Stochastic Predictive Control for Hybrid Vehicle Energy Management.

Kyle R. Williams

CoRR, 2018