Kyle R. Williams

Publication Activity (10 Years)

Years Active: 2021-2024
Publications (10 Years): 6

Top Topics

Continuous State Spaces

Markov Decision Problems

Motion Primitives

Reinforcement Learning

Top Venues

J. Aerosp. Inf. Syst.

IEEE Trans. Aerosp. Electron. Syst.

Publications

Zachary C. Goddard, Rithesh Rajasekar, Madhumita Mocharla, Garrett Manaster, Kyle R. Williams, Anirban Mazumdar
Leveraging Machine Learning for Generating and Utilizing Motion Primitives in Adversarial Environments. J. Aerosp. Inf. Syst. 21 (2) (2024)
Kyle R. Williams, Rachel Schlossman, Daniel Whitten, Joe Ingram, Srideep Musuvathy, James Pagan, Kyle A. Williams, Sam Green, Anirudh Patel, Anirban Mazumdar, Julie Parish
Trajectory Planning With Deep Reinforcement Learning in High-Level Action Spaces. IEEE Trans. Aerosp. Electron. Syst. 59 (3) (2023)
Zachary C. Goddard, Kenneth Wardlaw, Kyle R. Williams, Anirban Mazumdar
Selecting Minimal Motion Primitive Libraries with Genetic Algorithms. J. Aerosp. Inf. Syst. 20 (10) (2023)
Zachary C. Goddard, Kenneth Wardlaw, Kyle R. Williams, Julie Parish, Anirban Mazumdar
Utilizing Reinforcement Learning to Continuously Improve a Primitive-Based Motion Planner. J. Aerosp. Inf. Syst. 19 (7) (2022)
Kyle R. Williams, Rachel Schlossman, Daniel Whitten, Joe Ingram, Srideep Musuvathy, Anirudh Patel, James Pagan, Kyle A. Williams, Sam Green, Anirban Mazumdar, Julie Parish
Trajectory Planning with Deep Reinforcement Learning in High-Level Action Spaces. CoRR (2021)
Kyle R. Williams, J. Justin Wilbanks, Rachel Schlossman, David Kozlowski, Julie Parish
Dakota and Pyomo for Closed and Open Box Controller Gain Tuning. CDC (2021)