L4DC 2025

120 papers

“What Are My Options?": Explaining RL Agents with Diverse Near-Optimal Alternatives Noel Brindise, Vijeth Hebbar, Riya Shah, Cedric Langbort

$α$-RACER: Real-Time Algorithm for Game-Theoretic Motion Planning and Control in Autonomous Racing Using Near-Potential Function Dvij Kalaria, Chinmay Maheshwari, Shankar Sastry

A Dynamic Penalization Framework for Online Rank-1 Semidefinite Programming Relaxations Ahmad Al-Tawaha, Javad Lavaei, Ming Jin

A Dynamic Safety Shield for Safe and Efficient Reinforcement Learning of Navigation Tasks Murad Dawood, Ahmed Shokry, Maren Bennewitz

A Pontryagin Perspective on Reinforcement Learning Onno Eberhard, Claire Vernade, Michael Muehlebach

A Short Information-Theoretic Analysis of Linear Auto-Regressive Learning Ingvar Ziemann

A Theoretical Analysis of Soft-Label vs Hard-Label Training in Neural Networks Saptarshi Mandal, Xiaojun Lin, Rayadurgam Srikant

A-NC: Adaptive Neural Control with Implicit Online Inference of Privileged Parameters Marcin Paluch, Florian Bolli, Pehuen Moure, Xiang Deng, Tobi Delbruck

Abstraction-Based Control of Unknown Continuous-Space Models with Just Two Trajectories Behrad Samari, Mahdieh Zaker, Abolfazl Lavaei

Accelerating Proximal Policy Optimization Learning Using Task Prediction for Solving Environments with Delayed Rewards Ahmad Ahmad, Mehdi Kermanshah, Kevin Leahy, Zachary Serlin, Ho Chit Siu, Makai Mann, Cristian-Ioan Vasile, Roberto Tron, Calin Belta

Action-Conditioned Hamiltonian Generative Networks (AC-HGN) for Supervised and Reinforcement Learning Arne Troch, Kevin Mets, Siegfried Mercelis

Adaptive Control of Positive Systems with Application to Learning SSP Fethi Bencherki, Anders Rantzer

Analytical Integral Global Optimization Sebastien Labbe, Andrea Del Prete

Anytime Safe Reinforcement Learning Pol Mestres, Arnau Marzabal, Jorge Cortes

Approximate Thompson Sampling for Learning Linear Quadratic Regulators with $O(\sqrt{T})$ Regret Yeoneung Kim, Gihun Kim, Jiwhan Park, Insoon Yang

Asymptotics of Linear Regression with Linearly Dependent Data Behrad Moniri, Hamed Hassani

Automating the Loop in Traffic Incident Management on Highway Matteo Cercola, Nicola Gatti, Pedro Huertas Leyva, Benedetto Carambia, Simone Formentin

Back to Base: Towards Hands-Off Learning via Safe Resets with Reach-Avoid Safety Filters Azra Begzadic, Nikhil Shinde, Sander Tonkens, Dylan Hirsch, Kaleb Ugalde, Michael Yip, Jorge Cortes, Sylvia Herbert

BIGE : Biomechanics-Informed GenAI for Exercise Science Shubh Maheshwari, Anwesh Mohanty, Yadi Cao, Swithin Razu, Andrew McCulloch, Rose Yu

Bridging Adaptivity and Safety: Learning Agile Collision-Free Locomotion Across Varied Physics Yichao Zhong, Chong Zhang, Tairan He, Guanya Shi

Bridging Distributionally Robust Learning and Offline RL: An Approach to Mitigate Distribution Shift and Partial Data Coverage Kishan Panaganti, Zaiyan Xu, Dileep Kalathil, Mohammad Ghavamzadeh

CIKAN: Constraint Informed Kolmogorov-Arnold Networks for Autonomous Spacecraft Rendezvous Using Time Shift Governor Taehyeun Kim, Anouck Girard, Ilya Kolmanovsky

Computing Quasi-Nash Equilibria via Gradient-Response Schemes Zhuoyu Xiao, Uday V. Shanbhag

Conditional Kernel Imitation Learning for Continuous State Environments Rishabh Agrawal, Nathan Dahlin, Rahul Jain, Ashutosh Nayyar

Contingency Constrained Planning with MPPI Within MPPI Leonard Jung, Alexander Estornell, Michael Everett

Continual Learning and Lifting of Koopman Dynamics for Linear Control of Legged Robots Feihan Li, Abulikemu Abuduweili, Yifan Sun, Rui Chen, Weiye Zhao, Changliu Liu

Controlling Participation in Federated Learning with Feedback Michael Cummins, Guner Dilsad Er, Michael Muehlebach

Data-Driven and Stealthy Deactivation of Safety Filters Daniel Arnström, Andre M.H. Teixeira

Data-Driven Near-Optimal Control of Nonlinear Systems over Finite Horizon Vasanth Reddy Baddam, Hoda Eldardiry, Almuatazbellah Boker

Data-Driven Optimal Control of Unknown Nonlinear Dynamical Systems Using the Koopman Operator Zhexuan Zeng, Ruikun Zhou, Yiming Meng, Jun Liu

Data-Driven yet Formal Policy Synthesis for Stochastic Nonlinear Dynamical Systems Mahdi Nazeri, Thom Badings, Sadegh Soudjani, Alessandro Abate

Deep Source-Seekers with Obstacle Avoidance: Adaptive Hybrid Control with Transformers In-the-Loop Xiyuan Zhang, Daniel Ochoa, Regina Talonia, Jorge Poveda

DeePC-Hunt: Data-Enabled Predictive Control Hyperparameter Tuning via Differentiable Optimization Michael Cummins, Alberto Padoan, Keith Moffat, Florian Dorfler, John Lygeros

Dense Dynamics-Aware Reward Synthesis: Integrating Prior Experience with Demonstrations Cevahir Koprulu, Po-Han Li, Tianyu Qiu, Ruihan Zhao, Tyler Westenbroek, David Fridovich-Keil, Sandeep Chinchali, Ufuk Topcu

Diffusion Predictive Control with Constraints Ralf Römer, Alexander von Rohr, Angela Schoellig

DiffuSolve: Diffusion-Based Solver for Non-Convex Trajectory Optimization Anjian Li, Zihan Ding, Adji Bousso Dieng, Ryne Beeson

Disentangling Uncertainties by Learning Compressed Data Representation Zhiyu An, Zhibo Hou, Wan Du

DKMGP: A Gaussian Process Approach to Multi-Task and Multi-Step Vehicle Dynamics Modeling in Autonomous Racing Jingyun Ning, Madhur Behl

Domain Randomization Is Sample Efficient for Linear Quadratic Control Tesshu Fujinami, Bruce D. Lee, Nikolai Matni, George J. Pappas

Efficient Duple Perturbation Robustness in Low-Rank MDPs Yang Hu, Haitong Ma, Na Li, Bo Dai

Exploiting Approximate Symmetry for Efficient Multi-Agent Reinforcement Learning Batuhan Yardim, Niao He

Exploiting Inter-Agent Coupling Information for Efficient Reinforcement Learning of Cooperative LQR Shahbaz P Qadri Syed, He Bai

Extended Convex Lifting for Policy Optimization of Optimal and Robust Control Yang Zheng, Chih-Fan Pai, Yujie Tang

Fast and Reliable $n - K$ Contingency Screening with Input-Convex Neural Networks Nicolas Christianson, Wenqi Cui, Steven Low, Weiwei Yang, Baosen Zhang

Federated Posterior Sharing for Multi-Agent Systems in Uncertain Environments Yuxi Wang, Peng Wu, Mahdi Imani

Finite Sample Analysis of Tensor Decomposition for Learning Mixtures of Linear Systems Maryann Rui, Munther Dahleh

Finite Sample Identification of Partially Observed Bilinear Dynamical Systems Yahya Sattar, Yassir Jedra, Maryam Fazel, Sarah Dean

Flow Matching for Stochastic Linear Control Systems Yuhang Mei, Mohammad Al-Jarrah, Amirhossein Taghvaei, Yongxin Chen

Formation Shape Control Using the Gromov-Wasserstein Metric Haruto Nakashima, Siddhartha Ganguly, Kohei Morimoto, Kenji Kashima

Hybrid Modeling of Heterogeneous Human Teams for Collaborative Decision Processes Amirhossein Ravari, Seyede Fatemeh Ghoreishi, Tian Lan, Nathaniel D. Bastian, Mahdi Imani

HydroGym: A Reinforcement Learning Platform for Fluid Dynamics Christian Lagemann, Ludger Paehler, Jared Callaham, Sajeda Mokbel, Samuel Ahnert, Kai Lagemann, Esther Lagemann, Nikolaus Adams, Steven Brunton

Imperative MPC: An End-to-End Self-Supervised Learning with Differentiable MPC for UAV Attitude Control Haonan He, Yuheng Qiu, Junyi Geng

Informative Input Design for Dynamic Mode Decomposition Joshua Ott, Mykel Kochenderfer, Stephen Boyd

Interacting Particle Systems for Fast Linear Quadratic RL Anant A. Joshi, Heng-Sheng Chang, Amirhossein Taghvaei, Prashant G. Mehta, Sean P. Meyn

Interaction-Aware Parameter Privacy-Preserving Data Sharing in Coupled Systems via Particle Filter Reinforcement Learning Haokun Yu, Jingyuan Zhou, Kaidi Yang

Kernel-Based Optimal Control: An Infinitesimal Generator Approach Petar Bevanda, Nicolas Hoischen, Tobias Wittmann, Jan Brudigam, Sandra Hirche, Boris Houska

Koopman Based Trajectory Optimization with Mixed Boundaries Mohamed Abou-Taleb, Maximilian Raff, Kathrin Flaßkamp, C. David Remy

Learn with Imagination: Safe Set Guided State-Wise Constrained Policy Optimization Yifan Sun, Feihan Li, Weiye Zhao, Rui Chen, Tianhao Wei, Changliu Liu

Learning and Steering Game Dynamics Towards Desirable Outcomes Ilayda Canyakmaz, Iosif Sakos, Wayne Lin, Antonios Varvitsiotis, Georgios Piliouras

Learning Biomolecular Models Using Signal Temporal Logic Hanna Krasowski, Eric Palanques-Tost, Calin Belta, Murat Arcak

Learning Collective Dynamics of Multi-Agent Systems Using Event-Based Vision Minah Lee, Uday Kamal, Saibal Mukhopadhyay

Learning Feasible Transitions for Efficient Contact Planning Rikhat Akizhanov, Victor Dhedin, Majid Khadiv, Ivan Laptev

Learning for Layered Safety-Critical Control with Predictive Control Barrier Functions William D. Compton, Max H. Cohen, Aaron D. Ames

Learning Kolmogorov-Arnold Neural Activation Functions by Infinite-Dimensional Optimization Leon Khalyavin, Alessio Moreschini, Thomas Parisini

Learning Temporal Logic Predicates from Data with Statistical Guarantees Emi Soroka, Rohan Sinha, Sanjay Lall

Learning Two-Agent Motion Planning Strategies from Generalized Nash Equilibrium for Model Predictive Control Hansung Kim, Edward L. Zhu, Chang Seok Lim, Francesco Borrelli

Learning with Contextual Information in Non-Stationary Environments Sean Anderson, Joao P. Hespanha

Linear Supervision for Nonlinear, High-Dimensional Neural Control and Differential Games William Sharpless, Zeyuan Feng, Somil Bansal, Sylvia Herbert

Linear System Identification from Snapshot Data by Schrodinger Bridge Kohei Morimoto, Kenji Kashima

LiveNet: Robust, Minimally Invasive Multi-Robot Control for Safe and Live Navigation in Constrained Environments Srikar Gouru, Siddharth Lakkoju, Rohan Chandra

Logarithmic Regret for Nonlinear Control James Wang, Bruce Lee, Ingvar Ziemann, Nikolai Matni

Lyapunov Perception Contracts for Operating Design Domains Yangge Li, Chenxi Ji, Jai Anchalia, Yixuan Jia, Benjamin C Yang, Daniel Zhuang, Sayan Mitra

Meta-Learning for Adaptive Control with Automated Mirror Descent Sunbochen Tang, Haoyuan Sun, Navid Azizan

Mission-Driven Exploration for Accelerated Deep Reinforcement Learning with Temporal Logic Task Specifications Jun Wang, Hosein Hasanbeig, Kaiyuan Tan, Zihe Sun, Yiannis Kantaros

Morphological-Symmetry-Equivariant Heterogeneous Graph Neural Network for Robotic Dynamics Learning Fengze Xie, Sizhe Wei, Yue Song, Yisong Yue, Lu Gan

Multi-Agent Stochastic Bandits Robust to Adversarial Corruptions Fatemeh Ghaffari, Xuchuang Wang, Jinhang Zuo, Mohammad Hajiesmaili

Multi-Constraint Safe Reinforcement Learning via Closed-Form Solution for Log-Sum-Exp Approximation of Control Barrier Functions Chenggang Wang, Xinyi Wang, Yutong Dong, Lei Song, Xinping Guan

NAPI-MPC: Neural Accelerated Physics-Informed MPC for Nonlinear PDE Systems Peilun Li, Kaiyuan Tan, Thomas Beckers

Neural Contraction Metrics with Formal Guarantees for Discrete-Time Nonlinear Dynamical Systems Haoyu Li, Xiangru Zhong, Bin Hu, Huan Zhang

Neural Network-Assisted Interval Reachability for Systems with Control Barrier Function-Based Safe Controllers Damola Ajeyemi, Saber Jafarpour, Emiliano Dall’Anese

Neural Operators for Predictor Feedback Control of Nonlinear Delay Systems Luke Bhan, Peijia Qin, Miroslav Krstic, Yuanyuan Shi

Neuro-Symbolic Deadlock Resolution in Multi-Robot Systems Ruiyang Wang, Bowen He, Miroslav Pajic

Nonconvex Linear System Identification with Minimal State Representation Uday Kiran Reddy Tadipatri, Benjamin D. Haeffele, Joshua Agterberg, Ingvar Ziemann, Rene Vidal

Opt-ODENet: Neural ODE Controller Design with Differentiable Optimization Layers for Safety and Stability Keyan Miao, Liqun Zhao, Han Wang, Konstantinos Gatsis, Antonis Papachristodoulou

Orthogonal Projection-Based Regularization for Efficient Model Augmentation Bendeguz Mate Györök, Jan H. Hoekstra, Johan Kon, Tamas Peni, Maarten Schoukens, Roland Toth

Outlier-Robust Linear System Identification Under Heavy-Tailed Noise Vinay Kanakeri, Aritra Mitra

PACE: A Framework for Learning and Control in Linear Incomplete-Information Differential Games Seyed Yousef Soltanian, Wenlong Zhang

Physics-Enforced Reservoir Computing for Forecasting Spatiotemporal Systems Dima Tretiak, Anastasia Bizyaeva, J. Nathan Kutz, Steven L. Brunton

Physics-Informed Gaussian Processes as Linear Model Predictive Controller Jörn Tebbe, Andreas Besginow, Markus Lange-Hegermann

Predictive Monitoring of Black-Box Dynamical Systems Thomas A. Henzinger, Fabian Kresse, Kaushik Mallik, Emily Yu, \DJor\dje Žikelić

Probabilistic Satisfaction of Temporal Logic Constraints in Reinforcement Learning via Adaptive Policy-Switching Xiaoshan Lin, Sadik Bera Yuksel, Yasin Yazicioglu, Derya Aksaray

QP Based Constrained Optimization for Reliable PINN Training Alan Williams, Christopher Leon, Alexander Scheinker

Rates for Offline Reinforcement Learning with Adaptively Collected Data Sunil Madhow, Dan Qiao, Ming Yin, Yu-Xiang Wang

Realizable Continuous-Space Shields for Safe Reinforcement Learning Kyungmin Kim, Davide Corsi, Andoni Rodrı́guez, Jb Lanier, Benjami Parellada, Pierre Baldi, César Sánchez, Roy Fox

Reinforcement Learning from Multi-Level and Episodic Human Feedback Muhammad Qasim Elahi, Somtochukwu Oguchienti, Maheed H. Ahmed, Mahsa Ghasemi

Responding to Promises: No-Regret Learning Against Followers with Memory Vijeth Hebbar, Cedric Langbort

Robust Control of Uncertain Switched Affine Systems via Scenario Optimization Negar Monir, Mahdieh S. Sadabadi, Sadegh Soudjani

Robust Inverse Reinforcement Learning Control with Unknown States Bosen Lian, Wenqian Xue, Nhan Nguyen

Safe Cooperative Multi-Agent Reinforcement Learning with Function Approximation Hao-Lun Hsu, Miroslav Pajic

Safe Decision Transformer with Learning-Based Constraints Ruhan Wang, Dongruo Zhou

Safe Exploration in Reinforcement Learning: Training Backup Control Barrier Functions with Zero Training-Time Safety Violations Pedram Rabiee, Amirsaeid Safari

Safe Learning in the Real World via Adaptive Shielding with Hamilton-Jacobi Reachability Michael Lu, Jashanraj Gosain, Luna Sang, Mo Chen

Safe PDE Boundary Control with Neural Operators Hanjiang Hu, Changliu Liu

Safe, Out-of-Distribution-Adaptive MPC with Conformalized Neural Network Ensembles Jose Leopoldo Contreras, Ola Shorinwa, Mac Schwager

Scalability Enhancement and Data-Heterogeneity Awareness in Gradient Tracking Based Decentralized Bayesian Learning Kinjal Bhar, He Bai, Jemin George, Carl Busart

Scalable Natural Policy Gradient for General-Sum Linear Quadratic Games with Known Parameters Mostafa Shibl, Wesley Suttle, Vijay Gupta

Sensor Scheduling in Intrusion Detection Games with Uncertain Payoffs Jayanth Bhargav, Shreyas Sundaram, Mahsa Ghasemi

State Space Models, Emergence, and Ergodicity: How Many Parameters Are Needed for Stable Predictions? Ingvar Ziemann, Nikolai Matni, George Pappas

STLGame: Signal Temporal Logic Games in Adversarial Multi-Agent Systems Shuo Yang, Hongrui Zheng, Cristian-Ioan Vasile, George Pappas, Rahul Mangharam

Stochastic Real-Time Deception in Nash Equilibrium Seeking for Games with Quadratic Payoffs Michael Tang, Miroslav Krstic, Jorge Poveda

STRiDE: STate-Space Riemannian Diffusion for Equivariant Planning Evangelos Chatzipantazis, Nishanth Rao, Kostas Daniilidis

Symmetries-Enhanced Multi-Agent Reinforcement Learning Nikolaos Bousias, Stefanos Pertigkiozoglou, Kostas Daniilidis, George Pappas

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning Gokul Puthumanaillam, Jae Hyuk Song, Nurzhan Yesmagambet, Shinkyu Park, Melkior Ornik

TamedPUMA: Safe and Stable Imitation Learning with Geometric Fabrics Saray Bakker, Rodrigo Perez-Dattari, Cosimo Della Santina, Wendelin Böhmer, Javier Alonso-Mora

Temporal Logic Control for Nonlinear Stochastic Systems Under Unknown Disturbances Ibon Gracia, Luca Laurenti, Manuel Mazo Jr, Alessandro Abate, Morteza Lahijanian

The Complexity of Sequential Prediction in Dynamical Systems Vinod Raman, Unique Subedi, Ambuj Tewari

Topological State Space Inference for Dynamical Systems P K Mishal Assif, Yuliy Baryshnikov

Toward Near-Globally Optimal Nonlinear Model Predictive Control via Diffusion Models Tzu-Yuan Huang, Armin Lederer, Nicolas Hoischen, Jan Brudigam, Xuehua Xiao, Stefan Sosnowski, Sandra Hirche

WAVE: Wasserstein Adaptive Value Estimation for Actor-Critic Reinforcement Learning Ali Baheri, Zahra Shahrooei, Chirayu Salgarkar

Zero-Shot Sim-to-Real Transfer for Reinforcement Learning-Based Visual Servoing of Soft Continuum Arms Hsin-Jung Yang, Mahsa Khosravi, Benjamin Walt, Girish Krishnan, Soumik Sarkar