Subramanya Nageshrao

According to our database, Subramanya Nageshrao authored at least 30 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Toward Interpretable-AI Policies Using Evolutionary Nonlinear Decision Trees for Discrete-Action Systems.

Yashesh D. Dhebar, Kalyanmoy Deb, Subramanya Nageshrao, Ling Zhu, Dimitar P. Filev

IEEE Trans. Cybern., January, 2024

2023

A Risk-Averse Preview-Based Q-Learning Algorithm: Application to Highway Driving of Autonomous Vehicles.

Majid Mazouchi, Subramanya Nageshrao, Hamidreza Modares

IEEE Trans. Control. Syst. Technol., July, 2023

Interpretable Reinforcement Learning for Robotics and Continuous Control.

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

CoRR, 2023

2022

Game-Theoretic Lane-Changing Decision Making and Payoff Learning for Autonomous Vehicles.

Victor G. Lopez, Frank L. Lewis, Mushuang Liu, Yan Wan, Subramanya Nageshrao, Dimitar P. Filev

IEEE Trans. Veh. Technol., 2022

An Online Evolving Method For a Safe and Fast Automated Vehicle Control System.

Teawon Han, Subramanya Nageshrao, Dimitar P. Filev, Keith A. Redmill, Ümit Özgüner

IEEE Trans. Syst. Man Cybern. Syst., 2022

A Three-Level Game-Theoretic Decision-Making Framework for Autonomous Vehicles.

Mushuang Liu, Yan Wan, Frank L. Lewis, Subramanya Nageshrao, Dimitar P. Filev

IEEE Trans. Intell. Transp. Syst., 2022

Conflict-Aware Safe Reinforcement Learning: A Meta-Cognitive Learning Framework.

Majid Mazouchi, Subramanya Nageshrao, Hamidreza Modares

IEEE CAA J. Autom. Sinica, 2022

Robust AI Driving Strategy for Autonomous Vehicles.

Subramanya Nageshrao, Yousaf Rahman, Vladimir Ivanovic, Mrdjan Jankovic, H. Eric Tseng, Michael Hafner, Dimitar P. Filev

CoRR, 2022

2021

Explaining Deep Learning Models Through Rule-Based Approximation and Visualization.

Eduardo A. Soares, Plamen P. Angelov, Bruno Costa, Marcos Castro, Subramanya Nageshrao, Dimitar P. Filev

IEEE Trans. Fuzzy Syst., 2021

Finite-time Koopman Identifier: A Unified Batch-online Learning Framework for Joint Learning of Koopman Structure and Parameters.

Majid Mazouchi, Subramanya Nageshrao, Hamidreza Modares

CoRR, 2021

A Convex Programming Approach to Data-Driven Risk-Averse Reinforcement Learning.

Yuzhen Han, Majid Mazouchi, Subramanya Nageshrao, Hamidreza Modares

CoRR, 2021

Assured Learning-enabled Autonomy: A Metacognitive Reinforcement Learning Framework.

Aquib Mustafa, Majid Mazouchi, Subramanya Nageshrao, Hamidreza Modares

CoRR, 2021

Interpretable AI Agent Through Nonlinear Decision Trees for Lane Change Problem.

Abhiroop Ghosh, Yashesh D. Dhebar, Ritam Guha, Kalyanmoy Deb, Subramanya Nageshrao, Ling Zhu, H. Eric Tseng, Dimitar P. Filev

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2021

A One-shot Convex Optimization Approach to Risk-Averse Q-Learning.

Yuzhen Han, Majid Mazouchi, Subramanya Nageshrao, Hamidreza Modares

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

2020

Interpretable-AI Policies using Evolutionary Nonlinear Decision Trees for Discrete Action Systems.

Yashesh D. Dhebar, Kalyanmoy Deb, Subramanya Nageshrao, Ling Zhu, Dimitar P. Filev

CoRR, 2020

An online evolving framework for advancing reinforcement-learning based automated vehicle control.

Teawon Han, Subramanya Nageshrao, Dimitar P. Filev, Ümit Özgüner

CoRR, 2020

Deep Reinforcement Learning with Enhanced Safety for Autonomous Highway Driving.

Ali Baheri, Subramanya Nageshrao, H. Eric Tseng, Ilya V. Kolmanovsky, Anouck Girard, Dimitar P. Filev

Proceedings of the IEEE Intelligent Vehicles Symposium, 2020

Generating Socially Acceptable Perturbations for Efficient Evaluation of Autonomous Vehicles.

Songan Zhang, Huei Peng, Subramanya Nageshrao, H. Eric Tseng

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

Reinforcement learning based compensation methods for robot manipulators.

Yudha P. Pane, Subramanya Nageshrao, Jens Kober, Robert Babuska

Eng. Appl. Artif. Intell., 2019

Autonomous Highway Driving using Deep Reinforcement Learning.

Subramanya Nageshrao, H. Eric Tseng, Dimitar P. Filev

Proceedings of the 2019 IEEE International Conference on Systems, Man and Cybernetics, 2019

Discretionary Lane Change Decision Making using Reinforcement Learning with Model-Based Exploration.

Songan Zhang, Huei Peng, Subramanya Nageshrao, H. Eric Tseng

Proceedings of the 18th IEEE International Conference On Machine Learning And Applications, 2019

Explainable Density-Based Approach for Self-Driving Actions Classification.

Eduardo A. Soares, Plamen P. Angelov, Dimitar P. Filev, Bruno Costa, Marcos Castro, Subramanya Nageshrao

Proceedings of the 18th IEEE International Conference On Machine Learning And Applications, 2019

Interpretable Approximation of a Deep Reinforcement Learning Agent as a Set of If-Then Rules.

Subramanya Nageshrao, Bruno Costa, Dimitar P. Filev

Proceedings of the 18th IEEE International Conference On Machine Learning And Applications, 2019

2017

Model-based real-time control of a magnetic manipulator system.

Jan-Willem Damsteeg, Subramanya Nageshrao, Robert Babuska

Proceedings of the 56th IEEE Annual Conference on Decision and Control, 2017

2016

Online learning algorithms: For passivity-based and distributed control.

Subramanya Nageshrao

PhD thesis, 2016

Port-Hamiltonian Systems in Adaptive and Learning Control: A Survey.

Subramanya Nageshrao, Gabriel A. D. Lopes, Dimitri Jeltsema, Robert Babuska

IEEE Trans. Autom. Control., 2016

Optimal model-free output synchronization of heterogeneous systems using off-policy reinforcement learning.

Hamidreza Modares, Subramanya Nageshrao, Gabriel Alexandre Delgado Lopes, Robert Babuska, Frank L. Lewis

Autom., 2016

Actor-critic reinforcement learning for tracking control in robotics.

Yudha P. Pane, Subramanya Nageshrao, Robert Babuska

Proceedings of the 55th IEEE Conference on Decision and Control, 2016

2015

Reinforcement Learning for Port-Hamiltonian Systems.

Olivier Sprangers, Robert Babuska, Subramanya Nageshrao, Gabriel A. D. Lopes

IEEE Trans. Cybern., 2015

2014

Rapid learning in sequential composition control.

Esmaeil Najafi, Gabriel A. D. Lopes, Subramanya Nageshrao, Robert Babuska

Proceedings of the 53rd IEEE Conference on Decision and Control, 2014