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Wesley Suttle
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2020 – today
- 2024
- [c6]Wesley Suttle, Vipul Kumar Sharma, Krishna Chaitanya Kosaraju, Seetharaman Sivaranjani, Ji Liu, Vijay Gupta, Brian M. Sadler:
Sampling-based Safe Reinforcement Learning for Nonlinear Dynamical Systems. AISTATS 2024: 4420-4428 - [c5]Michael Y. Fatemi, Wesley A. Suttle, Brian M. Sadler:
Deceptive Path Planning via Reinforcement Learning with Graph Neural Networks. AAMAS 2024: 2258-2260 - [i11]Michael Y. Fatemi, Wesley A. Suttle, Brian M. Sadler:
Deceptive Path Planning via Reinforcement Learning with Graph Neural Networks. CoRR abs/2402.06552 (2024) - [i10]Wesley A. Suttle, Vipul K. Sharma, Krishna Chaitanya Kosaraju, S. Sivaranjani, Ji Liu, Vijay Gupta, Brian M. Sadler:
Sampling-based Safe Reinforcement Learning for Nonlinear Dynamical Systems. CoRR abs/2403.04007 (2024) - [i9]Bhrij Patel, Wesley A. Suttle, Alec Koppel, Vaneet Aggarwal, Brian M. Sadler, Amrit Singh Bedi, Dinesh Manocha:
Global Optimality without Mixing Time Oracles in Average-reward RL via Multi-level Actor-Critic. CoRR abs/2403.11925 (2024) - [i8]Utsav Singh, Wesley A. Suttle, Brian M. Sadler, Vinay P. Namboodiri, Amrit Singh Bedi:
PIPER: Primitive-Informed Preference-based Hierarchical Reinforcement Learning via Hindsight Relabeling. CoRR abs/2404.13423 (2024) - [i7]Utsav Singh, Souradip Chakraborty, Wesley A. Suttle, Brian M. Sadler, Vinay P. Namboodiri, Amrit Singh Bedi:
DIPPER: Direct Preference Optimization to Accelerate Primitive-Enabled Hierarchical Reinforcement Learning. CoRR abs/2406.10892 (2024) - 2023
- [c4]Wesley A. Suttle, Alec Koppel, Ji Liu:
Information-Directed Policy Search in Sparse-Reward Settings via the Occupancy Information Ratio. CISS 2023: 1-6 - [c3]Wesley A. Suttle, Amrit S. Bedi, Bhrij Patel, Brian M. Sadler, Alec Koppel, Dinesh Manocha:
Beyond Exponentially Fast Mixing in Average-Reward Reinforcement Learning via Multi-Level Monte Carlo Actor-Critic. ICML 2023: 33240-33267 - [i6]Wesley A. Suttle, Amrit Singh Bedi, Bhrij Patel, Brian M. Sadler, Alec Koppel, Dinesh Manocha:
Beyond Exponentially Fast Mixing in Average-Reward Reinforcement Learning via Multi-Level Monte Carlo Actor-Critic. CoRR abs/2301.12083 (2023) - [i5]Bhrij Patel, Kasun Weerakoon, Wesley A. Suttle, Alec Koppel, Brian M. Sadler, Amrit Singh Bedi, Dinesh Manocha:
Ada-NAV: Adaptive Trajectory-Based Sample Efficient Policy Learning for Robotic Navigation. CoRR abs/2306.06192 (2023) - 2022
- [j1]Krishna Chaitanya Kosaraju
, S. Sivaranjani
, Wesley Suttle
, Vijay Gupta
, Ji Liu
:
Reinforcement Learning Based Distributed Control of Dissipative Networked Systems. IEEE Trans. Control. Netw. Syst. 9(2): 856-866 (2022) - [c2]Wesley A. Suttle, Alec Koppel, Ji Liu:
Policy Gradient for Ratio Optimization: A Case Study. CISS 2022: 281-286 - [i4]Wesley A. Suttle, Alec Koppel, Ji Liu:
Occupancy Information Ratio: Infinite-Horizon, Information-Directed, Parameterized Policy Search. CoRR abs/2201.08832 (2022) - 2021
- [c1]Wesley Suttle, Kaiqing Zhang, Zhuoran Yang, Ji Liu, David N. Kraemer:
Reinforcement Learning for Cost-Aware Markov Decision Processes. ICML 2021: 9989-9999 - 2020
- [i3]Krishna Chaitanya Kosaraju, Seetharaman Sivaranjani, Wesley Suttle, Vijay Gupta
, J. Liu:
Reinforcement Learning based Distributed Control of Dissipative Networked Systems. CoRR abs/2011.14263 (2020)
2010 – 2019
- 2019
- [i2]Wesley Suttle, Zhuoran Yang, Kaiqing Zhang, Zhaoran Wang, Tamer Basar, Ji Liu:
A Multi-Agent Off-Policy Actor-Critic Algorithm for Distributed Reinforcement Learning. CoRR abs/1903.06372 (2019) - [i1]Wesley Suttle, Zhuoran Yang, Kaiqing Zhang, Ji Liu:
Stochastic Convergence Results for Regularized Actor-Critic Methods. CoRR abs/1907.06138 (2019)
Coauthor Index
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last updated on 2024-07-19 19:18 CEST by the dblp team
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