Rapid learning in sequential composition control. - Esmaeil Najafi; Gabriel A. D. Lopes; Subramanya Nageshrao; Robert Babuska (CDC, 2014)

Reinforcement Learning for Port-Hamiltonian Systems. - Olivier Sprangers; Robert Babuska; Subramanya Nageshrao; Gabriel A. D. Lopes (IEEE Trans. Cybern., 2015)

Actor-critic reinforcement learning for tracking control in robotics. - Yudha P. Pane; Subramanya Nageshrao; Robert Babuska (CDC, 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)

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)

Online learning algorithms: For passivity-based and distributed control. - Subramanya Nageshrao (2016)

Model-based real-time control of a magnetic manipulator system. - Jan-Willem Damsteeg; Subramanya Nageshrao; Robert Babuska (CDC, 2017)

Interpretable Approximation of a Deep Reinforcement Learning Agent as a Set of If-Then Rules. - Subramanya Nageshrao; Bruno Costa 004; Dimitar P. Filev (ICMLA, 2019)

Explainable Density-Based Approach for Self-Driving Actions Classification. - Eduardo A. Soares 001; Plamen Angelov 001; Dimitar P. Filev; Bruno Costa 004; Marcos Castro; Subramanya Nageshrao (ICMLA, 2019)

Discretionary Lane Change Decision Making using Reinforcement Learning with Model-Based Exploration. - Songan Zhang; Huei Peng; Subramanya Nageshrao; H. Eric Tseng (ICMLA, 2019)

Autonomous Highway Driving using Deep Reinforcement Learning. - Subramanya Nageshrao; H. Eric Tseng; Dimitar P. Filev (SMC, 2019)

Reinforcement learning based compensation methods for robot manipulators. - Yudha P. Pane; Subramanya Nageshrao; Jens Kober; Robert Babuska (Eng. Appl. Artif. Intell., 2019)

Generating Socially Acceptable Perturbations for Efficient Evaluation of Autonomous Vehicles. - Songan Zhang; Huei Peng; Subramanya Nageshrao; H. Eric Tseng (CVPR Workshops, 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 (IV, 2020)

An online evolving framework for advancing reinforcement-learning based automated vehicle control. - Teawon Han; Subramanya Nageshrao; Dimitar P. Filev; Ümit Özgüner (CoRR, 2020)

Interpretable-AI Policies using Evolutionary Nonlinear Decision Trees for Discrete Action Systems. - Yashesh D. Dhebar; Kalyanmoy Deb; Subramanya Nageshrao; Ling Zhu 001; Dimitar P. Filev (CoRR, 2020)

A One-shot Convex Optimization Approach to Risk-Averse Q-Learning. - Yuzhen Han; Majid Mazouchi; Subramanya Nageshrao; Hamidreza Modares (CDC, 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 001; H. Eric Tseng; Dimitar P. Filev (SSCI, 2021)

Assured Learning-enabled Autonomy: A Metacognitive Reinforcement Learning Framework. - Aquib Mustafa; 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)

Explaining Deep Learning Models Through Rule-Based Approximation and Visualization. - Eduardo A. Soares 001; Plamen P. Angelov; Bruno Costa 004; Marcos Castro; Subramanya Nageshrao; Dimitar P. Filev (IEEE Trans. Fuzzy Syst., 2021)

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)

Conflict-Aware Safe Reinforcement Learning: A Meta-Cognitive Learning Framework. - Majid Mazouchi; Subramanya Nageshrao; Hamidreza Modares (IEEE CAA J. Autom. Sinica, 2022)

A Three-Level Game-Theoretic Decision-Making Framework for Autonomous Vehicles. - Mushuang Liu; Yan Wan 001; Frank L. Lewis; Subramanya Nageshrao; Dimitar P. Filev (IEEE Trans. Intell. Transp. Syst., 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)

Game-Theoretic Lane-Changing Decision Making and Payoff Learning for Autonomous Vehicles. - Victor G. Lopez; Frank L. Lewis; Mushuang Liu; Yan Wan 001; Subramanya Nageshrao; Dimitar P. Filev (IEEE Trans. Veh. Technol., 2022)

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 075; Subramanya Nageshrao; et al. (CoRR, 2023)

Finite-time Koopman Identifier: A Unified Batch-online Learning Framework for Joint Learning of Koopman Structure and Parameters. - Majid Mazouchi; Subramanya Nageshrao; Hamidreza Modares (J. Mach. Learn. Res., 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., 2023)

Faster Model Predictive Control via Self-Supervised Initialization Learning. - Zhaoxin Li; Letian Chen; Rohan R. Paleja; Subramanya Nageshrao; Matthew C. Gombolay (CoRR, 2024)

Toward Interpretable-AI Policies Using Evolutionary Nonlinear Decision Trees for Discrete-Action Systems. - Yashesh D. Dhebar; Kalyanmoy Deb; Subramanya Nageshrao; Ling Zhu 001; Dimitar P. Filev (IEEE Trans. Cybern., 2024)

Hierarchical Game-Based Multi-Agent Decision-Making for Autonomous Vehicles. - Mushuang Liu; Yan Wan 001; Frank L. Lewis; Subramanya Nageshrao; H. Eric Tseng; Dimitar P. Filev (CoRR, 2025)