L4DC 2025

120 papers

Koopman Based Trajectory Optimization with Mixed Boundaries

Mohamed Abou-Taleb, Maximilian Raff, Kathrin Flaßkamp, C. David Remy

Data-Driven Yet Formal Policy Synthesis for Stochastic Nonlinear Dynamical Systems

Mahdi Nazeri, Thom Badings, Sadegh Soudjani, Alessandro Abate

Temporal Logic Control for Nonlinear Stochastic Systems Under Unknown Disturbances

Ibon Gracia, Luca Laurenti, Manuel Mazo Jr, Alessandro Abate, Morteza Lahijanian

Interaction-Aware Parameter Privacy-Preserving Data Sharing in Coupled Systems via Particle Filter Reinforcement Learning

Haokun Yu, Jingyuan Zhou, Kaidi Yang

Learning and steering game dynamics towards desirable outcomes

Ilayda Canyakmaz, Iosif Sakos, Wayne Lin, Antonios Varvitsiotis, Georgios Piliouras

Bridging Adaptivity and Safety: Learning Agile Collision-Free Locomotion Across Varied Physics

Yichao Zhong, Chong Zhang, Tairan He, Guanya Shi

TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning

Gokul Puthumanaillam, Jae Hyuk Song, Nurzhan Yesmagambet, Shinkyu Park, Melkior Ornik

Disentangling Uncertainties by Learning Compressed Data Representation

Zhiyu An, Zhibo Hou, Wan Du

Robust Control of Uncertain Switched Affine Systems via Scenario Optimization

Negar Monir, Mahdieh S. Sadabadi, Sadegh Soudjani

Neural Contraction Metrics with Formal Guarantees for Discrete-Time Nonlinear Dynamical Systems

Haoyu Li, Xiangru Zhong, Bin Hu, Huan Zhang

Physics-informed Gaussian Processes as Linear Model Predictive Controller

Jörn Tebbe, Andreas Besginow, Markus Lange-Hegermann

PACE: A Framework for Learning and Control in Linear Incomplete-Information Differential Games

Seyed Yousef Soltanian, Wenlong Zhang

Learning Collective Dynamics of Multi-Agent Systems using Event-based Vision

Minah Lee, Uday Kamal, Saibal Mukhopadhyay

Morphological-Symmetry-Equivariant Heterogeneous Graph Neural Network for Robotic Dynamics Learning

Fengze Xie, Sizhe Wei, Yue Song, Yisong Yue, Lu Gan

Exploiting inter-agent coupling information for efficient reinforcement learning of cooperative LQR

Shahbaz P Qadri Syed, He Bai

Learning Biomolecular Models using Signal Temporal Logic

Hanna Krasowski, Eric Palanques-Tost, Calin Belta, Murat Arcak

Safe Cooperative Multi-Agent Reinforcement Learning with Function Approximation

Hao-Lun Hsu, Miroslav Pajic

STRiDE: STate-space Riemannian Diffusion for Equivariant Planning

Evangelos Chatzipantazis, Nishanth Rao, Kostas Daniilidis

Safe Exploration in Reinforcement Learning: Training Backup Control Barrier Functions with Zero Training-Time Safety Violations

Pedram Rabiee, Amirsaeid Safari

Finite Sample Analysis of Tensor Decomposition for Learning Mixtures of Linear Systems

Maryann Rui, Munther Dahleh

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

Nonconvex Linear System Identification with Minimal State Representation

Uday Kiran Reddy Tadipatri, Benjamin D. Haeffele, Joshua Agterberg, Ingvar Ziemann, René Vidal

Finite Sample Identification of Partially Observed Bilinear Dynamical Systems

Yahya Sattar, Yassir Jedra, Maryam Fazel, Sarah Dean

Safe Learning in the Real World via Adaptive Shielding with Hamilton-Jacobi Reachability

Michael Lu, Jashanraj Gosain, Luna Sang, Mo Chen

BIGE : Biomechanics-informed GenAI for Exercise Science

Shubh Maheshwari, Anwesh Mohanty, Yadi Cao, Swithin Razu, Andrew McCulloch

NAPI-MPC: Neural Accelerated Physics-Informed MPC for Nonlinear PDE Systems

Peilun Li, Kaiyuan Tan, Thomas Beckers

Opt-ODENet: Neural ODE Controller Design with Differentiable Optimization Layers for Safety and Stability

Keyan Miao, Liqun Zhao, Han Wang, Konstantinos Gatsis, Antonis Papachristodoulou

Topological State Space Inference for Dynamical Systems

Mishal Assif P K, Yuliy Baryshnikov

“What are my options?": Explaining RL Agents with Diverse Near-Optimal Alternatives

Noel Brindise, Vijeth Hebbar, Riya Shah, Cedric Langbort

Reinforcement Learning from Multi-level and Episodic Human Feedback

Muhammad Qasim Elahi, Somtochukwu Oguchienti, Maheed H. Ahmed, Mahsa Ghasemi

Abstraction-Based Control of Unknown Continuous-Space Models with Just Two Trajectories

Behrad Samari, Mahdieh Zaker, Abolfazl Lavaei

Back to Base: Towards Hands-Off Learning via Safe Resets with Reach-Avoid Safety Filters

Azra Begzadić, Nikhil Shinde, Sander Tonkens, Dylan Hirsch, Kaleb Ugalde

Imperative MPC: An End-to-End Self-Supervised Learning with Differentiable MPC for UAV Attitude Control

Haonan He, Yuheng Qiu, Junyi Geng

Data-driven optimal control of unknown nonlinear dynamical systems using the Koopman operator

Zhexuan Zeng, Ruikun Zhou, Yiming Meng, Jun Liu

CIKAN: Constraint Informed Kolmogorov-Arnold Networks for Autonomous Spacecraft Rendezvous using Time Shift Governor

Taehyeun Kim, Anouck Girard, Ilya Kolmanovsky

STLGame: Signal Temporal Logic Games in Adversarial Multi-Agent Systems

Shuo Yang, Hongrui Zheng, Cristian-Ioan Vasile, George Pappas, Rahul Mangharam

QP Based Constrained Optimization for Reliable PINN Training

Alan Williams, Christopher Leon, Alexander Scheinker

A Theoretical Analysis of Soft-Label vs Hard-Label Training in Neural Networks

Saptarshi Mandal, Xiaojun Lin, Rayadurgam Srikant

Neuro-Symbolic Deadlock Resolution in Multi-Robot Systems

Ruiyang Wang, Bowen He, Miroslav Pajic

Lyapunov Perception Contracts for Operating Design Domains

Yangge Li, Chenxi Ji, Jai Anchalia, Yixuan Jia, Benjamin C Yang

Kernel-Based Optimal Control: An Infinitesimal Generator Approach

Petar Bevanda, Nicolas Hoischen, Tobias Wittmann, Jan Brüdigam, Sandra Hirche

Meta-Learning for Adaptive Control with Automated Mirror Descent

Sunbochen Tang, Haoyuan Sun, Navid Azizan

A Dynamic Penalization Framework for Online Rank-1 Semidefinite Programming Relaxations

Ahmad Al-Tawaha, Javad Lavaei, Ming Jin

Symmetries-enhanced Multi-Agent Reinforcement Learning

Nikolaos Bousias, Stefanos Pertigkiozoglou, Kostas Daniilidis, George Pappas

A-NC: Adaptive Neural Control with implicit online inference of privileged parameters

Marcin Paluch, Florian Bolli, Pehuen Moure, Xiang Deng, Tobi Delbruck

Neural Network-assisted Interval Reachability for Systems with Control Barrier Function-Based Safe Controllers

Damola Ajeyemi, Saber Jafarpour, Emiliano Dall’Anese

$α$-RACER: Real-Time Algorithm for Game-Theoretic Motion Planning and Control in Autonomous Racing using Near-Potential Function

Dvij Kalaria, Chinmay Maheshwari, Shankar Sastry

LiveNet: Robust, Minimally Invasive Multi-Robot Control for Safe and Live Navigation in Constrained Environments

Srikar Gouru, Siddharth Lakkoju, Rohan Chandra

Realizable Continuous-Space Shields for Safe Reinforcement Learning

KyungMin Kim, Davide Corsi, Andoni Rodrı́guez, JB Lanier, Benjami Parellada

WAVE: Wasserstein Adaptive Value Estimation for Actor-Critic Reinforcement Learning

Ali Baheri, Zahra Shahrooei, Chirayu Salgarkar

Domain Randomization is Sample Efficient for Linear Quadratic Control

Tesshu Fujinami, Bruce D. Lee, Nikolai Matni, George J. Pappas

Dense Dynamics-Aware Reward Synthesis: Integrating Prior Experience with Demonstrations

Cevahir Koprulu, Po-han Li, Tianyu Qiu, Ruihan Zhao, Tyler Westenbroek

Computing Quasi-Nash Equilibria via Gradient-Response Schemes

Zhuoyu Xiao, Uday V. Shanbhag

Contingency Constrained Planning with MPPI within MPPI

Leonard Jung, Alexander Estornell, Michael Everett

Learning with contextual information in non-stationary environments

Sean Anderson, Joao P. Hespanha

Deep Source-Seekers with Obstacle Avoidance: Adaptive Hybrid Control with Transformers In-The-Loop

Xiyuan Zhang, Daniel Ochoa, Regina Talonia, Jorge Poveda

Hybrid Modeling of Heterogeneous Human Teams for Collaborative Decision Processes

Amirhossein Ravari, Seyede Fatemeh Ghoreishi, Tian Lan, Nathaniel D. Bastian, Mahdi Imani

Federated Posterior Sharing for Multi-Agent Systems in Uncertain Environments

Yuxi Wang, Peng Wu, Mahdi Imani

Predictive Monitoring of Black-Box Dynamical Systems

Thomas A. Henzinger, Fabian Kresse, Kaushik Mallik, Emily Yu, \DJor\dje Žikelić

Diffusion Predictive Control with Constraints

Ralf Römer, Alexander von Rohr, Angela Schoellig

Toward Near-Globally Optimal Nonlinear Model Predictive Control via Diffusion Models

Tzu-Yuan Huang, Armin Lederer, Nicolas Hoischen, Jan Brüdigam, Xuehua Xiao

Mission-driven Exploration for Accelerated Deep Reinforcement Learning with Temporal Logic Task Specifications

Jun Wang, Hosein Hasanbeig, Kaiyuan Tan, Zihe Sun, Yiannis Kantaros

Robust Inverse Reinforcement Learning Control with Unknown States

Bosen Lian, Wenqian Xue, Nhan Nguyen

Probabilistic Satisfaction of Temporal Logic Constraints in Reinforcement Learning via Adaptive Policy-Switching

Xiaoshan Lin, Sadik Bera Yuksel, Yasin Yazicioglu, Derya Aksaray

Efficient Duple Perturbation Robustness in Low-rank MDPs

Yang Hu, Haitong Ma, Na Li, Bo Dai

Analytical Integral Global Optimization

Sebastien Labbe, Andrea Del Prete

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

A Dynamic Safety Shield for Safe and Efficient Reinforcement Learning of Navigation Tasks

Murad Dawood, Ahmed Shokry, Maren Bennewitz

DeePC-Hunt: Data-enabled Predictive Control Hyperparameter Tuning via Differentiable Optimization

Michael Cummins, Alberto Padoan, Keith Moffat, Florian Dorfler, John Lygeros

Adaptive Control of Positive Systems with Application to Learning SSP

Fethi Bencherki, Anders Rantzer

Responding to Promises: No-regret learning against followers with memory

Vijeth Hebbar, Cedric Langbort

Stochastic Real-Time Deception in Nash Equilibrium Seeking for Games with Quadratic Payoffs

Michael Tang, Miroslav Krstic, Jorge Poveda

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

Sensor Scheduling in Intrusion Detection Games with Uncertain Payoffs

Jayanth Bhargav, Shreyas Sundaram, Mahsa Ghasemi

Scalability Enhancement and Data-Heterogeneity Awareness in Gradient Tracking based Decentralized Bayesian Learning

Kinjal Bhar, He Bai, Jemin George, Carl Busart

Linear System Identification from Snapshot Data by Schrodinger bridge

Kohei Morimoto, Kenji Kashima

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

Logarithmic Regret for Nonlinear Control

James Wang, Bruce Lee, Ingvar Ziemann, Nikolai Matni

Outlier-Robust Linear System Identification Under Heavy-Tailed Noise

Vinay Kanakeri, Aritra Mitra

Fast and Reliable $N - k$ Contingency Screening with Input-Convex Neural Networks

Nicolas Christianson, Wenqi Cui, Steven Low, Weiwei Yang, Baosen Zhang

Safe PDE Boundary Control with Neural Operators

Hanjiang Hu, Changliu Liu

HydroGym: A Reinforcement Learning Platform for Fluid Dynamics

Christian Lagemann, Ludger Paehler, Jared Callaham, Sajeda Mokbel, Samuel Ahnert

Flow matching for stochastic linear control systems

Yuhang Mei, Mohammad Al-Jarrah, Amirhossein Taghvaei, Yongxin Chen

Conditional Kernel Imitation Learning for Continuous State Environments

Rishabh Agrawal, Nathan Dahlin, Rahul Jain, Ashutosh Nayyar

Data-Driven and Stealthy Deactivation of Safety Filters

Daniel Arnström, Andre M.H. Teixeira

Learning Kolmogorov-Arnold Neural Activation Functions by Infinite-Dimensional Optimization

Leon Khalyavin, Alessio Moreschini, Thomas Parisini

Learning Feasible Transitions for Efficient Contact Planning

Rikhat Akizhanov, Victor Dhedin, Majid Khadiv, Ivan Laptev

Data-Driven Near-Optimal Control of Nonlinear Systems Over Finite Horizon

Vasanth Reddy Baddam, Hoda Eldardiry, Almuatazbellah Boker

TamedPUMA: safe and stable imitation learning with geometric fabrics

Saray Bakker, Rodrigo Perez-Dattari, Cosimo Della Santina, Wendelin Böhmer, Javier Alonso-Mora

Extended Convex Lifting for Policy Optimization of Optimal and Robust Control

Yang Zheng, Chih-Fan Pai, Yujie Tang

Approximate Thompson Sampling for Learning Linear Quadratic Regulators with O(√T) Regret

Yeoneung Kim, Gihun Kim, Jiwhan Park, Insoon Yang

Linear Supervision for Nonlinear, High-Dimensional Neural Control and Differential Games

William Sharpless, Zeyuan Feng, Somil Bansal, Sylvia Herbert

Physics-Enforced Reservoir Computing for Forecasting Spatiotemporal Systems

Dima Tretiak, Anastasia Bizyaeva, J. Nathan Kutz, Steven L. Brunton

Informative Input Design for Dynamic Mode Decomposition

Joshua Ott, Mykel Kochenderfer, Stephen Boyd

Action-Conditioned Hamiltonian Generative Networks (AC-HGN) for Supervised and Reinforcement Learning

Arne Troch, Kevin Mets, Siegfried Mercelis

Learn With Imagination: Safe Set Guided State-wise Constrained Policy Optimization

Yifan Sun, Feihan Li, Weiye Zhao, Rui Chen, Tianhao Wei

Automating the loop in traffic incident management on highway

Matteo Cercola, Nicola Gatti, Pedro Huertas Leyva, Benedetto Carambia, Simone Formentin

Rates for Offline Reinforcement Learning with Adaptively Collected Data

Sunil Madhow, Dan Qiao, Ming Yin, Yu-Xiang Wang

Safe Decision Transformer with Learning-based Constraints

Ruhan Wang, Dongruo Zhou

A Pontryagin Perspective on Reinforcement Learning

Onno Eberhard, Claire Vernade, Michael Muehlebach