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Subramanya Nageshrao
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2020 – today
- 2024
- [j12]Yashesh D. Dhebar
, Kalyanmoy Deb
Toward Interpretable-AI Policies Using Evolutionary Nonlinear Decision Trees for Discrete-Action Systems. IEEE Trans. Cybern. 54(1): 50-62 (2024) - [i12]Zhaoxin Li, Letian Chen, Rohan R. Paleja, Subramanya Nageshrao, Matthew C. Gombolay:
Faster Model Predictive Control via Self-Supervised Initialization Learning. CoRR abs/2408.03394 (2024) - 2023
- [j11]Majid Mazouchi, Subramanya Nageshrao, Hamidreza Modares:
Finite-time Koopman Identifier: A Unified Batch-online Learning Framework for Joint Learning of Koopman Structure and Parameters. J. Mach. Learn. Res. 24: 336:1-336:35 (2023) - [j10]Majid Mazouchi
A Risk-Averse Preview-Based Q-Learning Algorithm: Application to Highway Driving of Autonomous Vehicles. IEEE Trans. Control. Syst. Technol. 31(4): 1803-1818 (2023) - [i11]Rohan R. Paleja, Letian Chen, Yaru Niu, Andrew Silva, Zhaoxin Li, Songan Zhang, Chace Ritchie, Sugju Choi, Kimberlee Chestnut Chang, Hongtei Eric Tseng, Yan Wang, Subramanya Nageshrao, Matthew C. Gombolay:
Interpretable Reinforcement Learning for Robotics and Continuous Control. CoRR abs/2311.10041 (2023) - 2022
- [j9]Majid Mazouchi, Subramanya Nageshrao, Hamidreza Modares:
Conflict-Aware Safe Reinforcement Learning: A Meta-Cognitive Learning Framework. IEEE CAA J. Autom. Sinica 9(3): 466-481 (2022) - [j8]Mushuang Liu
A Three-Level Game-Theoretic Decision-Making Framework for Autonomous Vehicles. IEEE Trans. Intell. Transp. Syst. 23(11): 20298-20308 (2022) - [j7]Teawon Han
An Online Evolving Method For a Safe and Fast Automated Vehicle Control System. IEEE Trans. Syst. Man Cybern. Syst. 52(9): 5723-5735 (2022) - [j6]Victor G. Lopez
Game-Theoretic Lane-Changing Decision Making and Payoff Learning for Autonomous Vehicles. IEEE Trans. Veh. Technol. 71(4): 3609-3620 (2022) - [i10]Subramanya Nageshrao, Yousaf Rahman, Vladimir Ivanovic, Mrdjan Jankovic, H. Eric Tseng, Michael Hafner, Dimitar P. Filev:
Robust AI Driving Strategy for Autonomous Vehicles. CoRR abs/2207.07829 (2022) - 2021
- [j5]Eduardo A. Soares
Explaining Deep Learning Models Through Rule-Based Approximation and Visualization. IEEE Trans. Fuzzy Syst. 29(8): 2399-2407 (2021) - [c11]Yuzhen Han, Majid Mazouchi, Subramanya Nageshrao, Hamidreza Modares:
A One-shot Convex Optimization Approach to Risk-Averse Q-Learning. CDC 2021: 102-107 - [c10]Abhiroop Ghosh
Interpretable AI Agent Through Nonlinear Decision Trees for Lane Change Problem. SSCI 2021: 1-8 - [i9]Aquib Mustafa, Majid Mazouchi, Subramanya Nageshrao, Hamidreza Modares:
Assured Learning-enabled Autonomy: A Metacognitive Reinforcement Learning Framework. CoRR abs/2103.12558 (2021) - [i8]Yuzhen Han, Majid Mazouchi, Subramanya Nageshrao, Hamidreza Modares:
A Convex Programming Approach to Data-Driven Risk-Averse Reinforcement Learning. CoRR abs/2103.14606 (2021) - [i7]Majid Mazouchi, Subramanya Nageshrao, Hamidreza Modares:
Finite-time Koopman Identifier: A Unified Batch-online Learning Framework for Joint Learning of Koopman Structure and Parameters. CoRR abs/2105.05903 (2021) - [i6]Majid Mazouchi, Subramanya Nageshrao, Hamidreza Modares:
A Risk-Averse Preview-based Q-Learning Algorithm: Application to Highway Driving of Autonomous Vehicles. CoRR abs/2112.03232 (2021) - 2020
- [c9]Songan Zhang, Huei Peng, Subramanya Nageshrao, H. Eric Tseng:
Generating Socially Acceptable Perturbations for Efficient Evaluation of Autonomous Vehicles. CVPR Workshops 2020: 1341-1347 - [c8]Ali Baheri, Subramanya Nageshrao, H. Eric Tseng, Ilya V. Kolmanovsky
Deep Reinforcement Learning with Enhanced Safety for Autonomous Highway Driving. IV 2020: 1550-1555 - [i5]Songan Zhang, Huei Peng, Subramanya Nageshrao, H. Eric Tseng:
Generating Socially Acceptable Perturbations for Efficient Evaluation of Autonomous Vehicles. CoRR abs/2003.08034 (2020) - [i4]Teawon Han, Subramanya Nageshrao, Dimitar P. Filev, Ümit Özgüner:
An online evolving framework for advancing reinforcement-learning based automated vehicle control. CoRR abs/2006.08092 (2020) - [i3]Yashesh D. Dhebar, Kalyanmoy Deb, Subramanya Nageshrao, Ling Zhu, Dimitar P. Filev:
Interpretable-AI Policies using Evolutionary Nonlinear Decision Trees for Discrete Action Systems. CoRR abs/2009.09521 (2020)
2010 – 2019
- 2019
- [j4]Yudha P. Pane
Reinforcement learning based compensation methods for robot manipulators. Eng. Appl. Artif. Intell. 78: 236-247 (2019) - [c7]Subramanya Nageshrao, Bruno Costa, Dimitar P. Filev:
Interpretable Approximation of a Deep Reinforcement Learning Agent as a Set of If-Then Rules. ICMLA 2019: 216-221 - [c6]Eduardo A. Soares, Plamen Angelov, Dimitar P. Filev, Bruno Costa, Marcos Castro, Subramanya Nageshrao:
Explainable Density-Based Approach for Self-Driving Actions Classification. ICMLA 2019: 469-474 - [c5]Songan Zhang, Huei Peng, Subramanya Nageshrao, H. Eric Tseng:
Discretionary Lane Change Decision Making using Reinforcement Learning with Model-Based Exploration. ICMLA 2019: 844-850 - [c4]Subramanya Nageshrao, H. Eric Tseng, Dimitar P. Filev:
Autonomous Highway Driving using Deep Reinforcement Learning. SMC 2019: 2326-2331 - [i2]Subramanya Nageshrao, H. Eric Tseng, Dimitar P. Filev:
Autonomous Highway Driving using Deep Reinforcement Learning. CoRR abs/1904.00035 (2019) - [i1]Ali Baheri, Subramanya Nageshrao, H. Eric Tseng, Ilya V. Kolmanovsky
Deep Reinforcement Learning with Enhanced Safety for Autonomous Highway Driving. CoRR abs/1910.12905 (2019) - 2017
- [c3]Jan-Willem Damsteeg, Subramanya Nageshrao, Robert Babuska:
Model-based real-time control of a magnetic manipulator system. CDC 2017: 3277-3282 - 2016
- [b1]Subramanya Nageshrao:
Online learning algorithms: For passivity-based and distributed control. Delft University of Technology, Netherlands, 2016 - [j3]Hamidreza Modares, Subramanya Nageshrao, Gabriel Alexandre Delgado Lopes, Robert Babuska, Frank L. Lewis:
Optimal model-free output synchronization of heterogeneous systems using off-policy reinforcement learning. Autom. 71: 334-341 (2016) - [j2]Subramanya Nageshrao, Gabriel A. D. Lopes, Dimitri Jeltsema, Robert Babuska:
Port-Hamiltonian Systems in Adaptive and Learning Control: A Survey. IEEE Trans. Autom. Control. 61(5): 1223-1238 (2016) - [c2]Yudha P. Pane
Actor-critic reinforcement learning for tracking control in robotics. CDC 2016: 5819-5826 - 2015
- [j1]Olivier Sprangers, Robert Babuska, Subramanya Nageshrao, Gabriel A. D. Lopes:
Reinforcement Learning for Port-Hamiltonian Systems. IEEE Trans. Cybern. 45(5): 1003-1013 (2015) - 2014
- [c1]Esmaeil Najafi
Rapid learning in sequential composition control. CDC 2014: 5171-5176
Coauthor Index
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last updated on 2024-09-14 01:11 CEST by the dblp team
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