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Kyle R. Williams

Kyle Richard Williams

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affiliation: Sandia National Laboratories, Albuquerque, NM, USA
affiliation (PhD 2018): Purdue University, West Lafayette, IN, USA

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2020 – today

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2024
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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): 127-139 (2024)
2023
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Zachary C. Goddard, Kenneth Wardlaw, Kyle R. Williams, Anirban Mazumdar:
Selecting Minimal Motion Primitive Libraries with Genetic Algorithms. J. Aerosp. Inf. Syst. 20(10): 618-626 (2023)
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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): 2513-2529 (2023)
2022
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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): 468-479 (2022)
2021
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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: 4854-4860
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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 abs/2110.00044 (2021)

2010 – 2019

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2018
[i1]
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  - journals/corr/abs-1804-08766
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Kyle R. Williams:
Real-Time Stochastic Predictive Control for Hybrid Vehicle Energy Management. CoRR abs/1804.08766 (2018)

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