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ORCID7th L4DC 2025: Ann Arbor, MI, USA
- Necmiye Ozay, Laura Balzano, Dimitra Panagou, Alessandro Abate:
7th Annual Learning for Dynamics & Control Conference, Ann Arbor, MI, USA, 4-6 June 2025. Proceedings of Machine Learning Research 283, PMLR 2025 - Ingvar M. Ziemann, Nikolai Matni, George J. Pappas:
State space models, emergence, and ergodicity: How many parameters are needed for stable predictions? 1-11 - Fatemeh Ghaffari, Xuchuang Wang, Jinhang Zuo, Mohammad Hajiesmaili:
Multi-agent Stochastic Bandits Robust to Adversarial Corruptions. 12-25 - Ingvar M. Ziemann:
A Short Information-Theoretic Analysis of Linear Auto-Regressive Learning. 26-30 - Batuhan Yardim, Niao He:
Exploiting Approximate Symmetry for Efficient Multi-Agent Reinforcement Learning. 31-44 - Anjian Li, Zihan Ding, Adji Bousso Dieng, Ryne Beeson:
DiffuSolve: Diffusion-based Solver for Non-convex Trajectory Optimization. 45-58 - Jingyun Ning, Madhur Behl:
DKMGP: A Gaussian Process Approach to Multi-Task and Multi-Step Vehicle Dynamics Modeling in Autonomous Racing. 59-71 - Behrad Moniri, Hamed Hassani:
Asymptotics of Linear Regression with Linearly Dependent Data. 72-85 - Emi Soroka, Rohan Sinha, Sanjay Lall:
Learning Temporal Logic Predicates from Data with Statistical Guarantees. 86-98 - Anant A. Joshi, Heng-Sheng Chang, Amirhossein Taghvaei, Prashant G. Mehta, Sean P. Meyn:
Interacting Particle Systems for Fast Linear Quadratic RL. 99-111 - Hansung Kim, Edward L. Zhu, Chang Seok Lim, Francesco Borrelli:
Learning Two-agent Motion Planning Strategies from Generalized Nash Equilibrium for Model Predictive Control. 112-123 - Vinod Raman, Unique Subedi, Ambuj Tewari:
The Complexity of Sequential Prediction in Dynamical Systems. 124-138 - Feihan Li, Abulikemu Abuduweili, Yifan Sun, Rui Chen, Weiye Zhao, Changliu Liu:
Continual Learning and Lifting of Koopman Dynamics for Linear Control of Legged Robots. 136-148 - Mostafa M. Shibl, Wesley Suttle, Vijay Gupta:
Scalable Natural Policy Gradient for General-Sum Linear Quadratic Games with Known Parameters. 139-152 - William D. Compton, Max H. Cohen, Aaron D. Ames:
Learning for Layered Safety-Critical Control with Predictive Control Barrier Functions. 153-165 - Bendegúz M. Györök, Jan H. Hoekstra, Johan Kon, Tamas Peni, Maarten Schoukens, Roland Tóth:
Orthogonal projection-based regularization for efficient model augmentation. 166-178 - Michael Cummins, Guner Dilsad Er, Michael Muehlebach:
Controlling Participation in Federated Learning with Feedback. 174-186 - Luke Bhan, Peijia Qin, Miroslav Krstic, Yuanyuan Shi:
Neural Operators for Predictor Feedback Control of Nonlinear Delay Systems. 179-193 - Jose Leopoldo Contreras, Ola Shorinwa, Mac Schwager:
Safe, Out-of-Distribution-Adaptive MPC with Conformalized Neural Network Ensembles. 194-207 - Haruto Nakashima, Siddhartha Ganguly, Kohei Morimoto, Kenji Kashima:
Formation Shape Control using the Gromov-Wasserstein Metric. 208-220 - Pol Mestres, Arnau Marzabal, Jorge Cortés:
Anytime Safe Reinforcement Learning. 221-232 - Onno Eberhard, Claire Vernade, Michael Muehlebach:
A Pontryagin Perspective on Reinforcement Learning. 233-244 - Ruhan Wang, Dongruo Zhou:
Safe Decision Transformer with Learning-based Constraints. 245-258 - Sunil Madhow, Dan Qiao, Ming Yin, Yuxiang Wang:
Rates for Offline Reinforcement Learning with Adaptively Collected Data. 259-271 - Matteo Cercola, Nicola Gatti, Pedro Huertas-Leyva, Benedetto Carambia, Simone Formentin:
Automating the loop in traffic incident management on highway. 272-284 - Yifan Sun, Feihan Li, Weiye Zhao, Rui Chen, Tianhao Wei, Changliu Liu:
Learn With Imagination: Safe Set Guided State-wise Constrained Policy Optimization. 298-309 - Arne Troch, Kevin Mets, Siegfried Mercelis:
Action-Conditioned Hamiltonian Generative Networks (AC-HGN) for Supervised and Reinforcement Learning. 310-322 - Joshua Ott, Mykel J. Kochenderfer, Stephen Boyd:
Informative Input Design for Dynamic Mode Decomposition. 336-349 - Dima Tretiak, Anastasia Bizyaeva, J. Nathan Kutz, Steven L. Brunton:
Physics-Enforced Reservoir Computing for Forecasting Spatiotemporal Systems. 350-364 - Will Sharpless, Zeyuan Feng, Somil Bansal, Sylvia L. Herbert:
Linear Supervision for Nonlinear, High-Dimensional Neural Control and Differential Games. 365-377 - Yeoneung Kim, Gihun Kim, Jiwhan Park, Insoon Yang:
Approximate Thompson Sampling for Learning Linear Quadratic Regulators with $O(\sqrt{T})$ Regret. 378-391 - Yang Zheng, Chih-Fan Pai, Yujie Tang:
Extended Convex Lifting for Policy Optimization of Optimal and Robust Control. 392-404 - Saray Bakker, Rodrigo Pérez-Dattari, Cosimo Della Santina, Wendelin Böhmer, Javier Alonso-Mora:
TamedPUMA: safe and stable imitation learning with geometric fabrics. 405-418 - Vasanth Reddy Baddam, Hoda Eldardiry, Almuatazbellah Boker:
Data-Driven Near-Optimal Control of Nonlinear Systems Over Finite Horizon. 419-430 - Rikhat Akizhanov, Victor Dhédin, Majid Khadiv, Ivan Laptev:
Learning Feasible Transitions for Efficient Contact Planning. 431-442 - Leon Khalyavin, Alessio Moreschini, Thomas Parisini:
Learning Kolmogorov-Arnold Neural Activation Functions by Infinite-Dimensional Optimization. 443-455 - Daniel Arnström, André M. H. Teixeira:
Data-Driven and Stealthy Deactivation of Safety Filters. 456-468 - Rishabh Agrawal, Nathan Dahlin, Rahul Jain, Ashutosh Nayyar:
Conditional Kernel Imitation Learning for Continuous State Environments. 469-483 - Yuhang Mei, Mohammad Al-Jarrah, Amirhossein Taghvaei, Yongxin Chen:
Flow matching for stochastic linear control systems. 484-496 - Christian Lagemann, Ludger Paehler, Jared Callaham, Sajeda Mokbel, Samuel Ahnert, Kai Lagemann, Esther Lagemann, Nikolaus A. Adams, Steven L. Brunton:
HydroGym: A Reinforcement Learning Platform for Fluid Dynamics. 497-512 - Hanjiang Hu, Changliu Liu:
Safe PDE Boundary Control with Neural Operators. 513-526 - Nicolas Christianson, Wenqi Cui, Steven H. Low, Weiwei Yang, Baosen Zhang:
Fast and Reliable N - k Contingency Screening with Input-Convex Neural Networks. 527-539 - Vinay Kanakeri, Aritra Mitra:
Outlier-Robust Linear System Identification Under Heavy-Tailed Noise. 540-551 - James Wang, Bruce D. Lee, Ingvar M. Ziemann, Nikolai Matni:
Logarithmic Regret for Nonlinear Control. 552-565 - Ahmad Ahmad, Mehdi Kermanshah, Kevin Leahy, Zachary Serlin, Ho Chit Siu, Makai Mann, Cristian-Ioan Vasile, Roberto Tron, Calin Belta:
Accelerating Proximal Policy Optimization Learning Using Task Prediction for Solving Environments with Delayed Rewards. 566-578 - Kohei Morimoto, Kenji Kashima:
Linear System Identification from Snapshot Data by Schrodinger bridge. 579-590 - Kinjal Bhar, He Bai, Jemin George, Carl E. Busart:
Scalability Enhancement and Data-Heterogeneity Awareness in Gradient Tracking based Decentralized Bayesian Learning. 591-605 - Jayanth Bhargav, Shreyas Sundaram, Mahsa Ghasemi:
Sensor Scheduling in Intrusion Detection Games with Uncertain Payoffs. 606-618 - Kishan Panaganti, Zaiyan Xu, Dileep Kalathil, Mohammad Ghavamzadeh:
Bridging Distributionally Robust Learning and Offline RL: An Approach to Mitigate Distribution Shift and Partial Data Coverage. 619-634 - Michael Tang, Miroslav Krstic, Jorge Poveda:
Stochastic Real-Time Deception in Nash Equilibrium Seeking for Games with Quadratic Payoffs. 635-646 - Vijeth Hebbar, Cedric Langbort:
Responding to Promises: No-regret learning against followers with memory. 647-659 - Fethi Bencherki, Anders Rantzer:
Adaptive Control of Positive Systems with Application to Learning SSP. 660-672 - Michael Cummins, Alberto Padoan, Keith Moffat, Florian Dörfler, John Lygeros:
DeePC-Hunt: Data-enabled Predictive Control Hyperparameter Tuning via Differentiable Optimization. 673-685 - Murad Dawood, Ahmed Shokry, Maren Bennewitz:
A Dynamic Safety Shield for Safe and Efficient Reinforcement Learning of Navigation Tasks. 686-697 - Chenggang Wang, Xinyi Wang, Yutong Dong, Lei Song, Xinping Guan:
Multi-Constraint Safe Reinforcement Learning via Closed-form Solution for Log-Sum-Exp Approximation of Control Barrier Functions. 698-710 - Sébastien Labbé, Andrea Del Prete:
Analytical Integral Global Optimization. 711-722 - Yang Hu, Haitong Ma, Na Li, Bo Dai:
Efficient Duple Perturbation Robustness in Low-rank MDPs. 723-737 - Xiaoshan Lin, Sadik Bera Yüksel, Yasin Yazicioglu, Derya Aksaray:
Probabilistic Satisfaction of Temporal Logic Constraints in Reinforcement Learning via Adaptive Policy-Switching. 738-749 - Bosen Lian, Wenqian Xue, Nhan Nguyen:
Robust Inverse Reinforcement Learning Control with Unknown States. 750-762 - Jun Wang, Hosein Hasanbeig, Kaiyuan Tan, Zihe Sun, Yiannis Kantaros:
Mission-driven Exploration for Accelerated Deep Reinforcement Learning with Temporal Logic Task Specifications. 763-776 - Tzu-Yuan Huang, Armin Lederer, Nicolas Hoischen, Jan Brüdigam, Xuehua Xiao, Stefan Sosnowski, Sandra Hirche:
Toward Near-Globally Optimal Nonlinear Model Predictive Control via Diffusion Models. 777-790 - Ralf Römer, Alexander von Rohr, Angela P. Schoellig:
Diffusion Predictive Control with Constraints. 791-803 - Thomas A. Henzinger, Fabian Kresse, Kaushik Mallik, Emily Yu, Djordje Zikelic:
Predictive Monitoring of Black-Box Dynamical Systems. 804-816 - Yuxi Wang, Peng Wu, Mahdi Imani:
Federated Posterior Sharing for Multi-Agent Systems in Uncertain Environments. 817-829 - Amirhossein Ravari, Seyede Fatemeh Ghoreishi, Tian Lan, Nathaniel D. Bastian, Mahdi Imani:
Hybrid Modeling of Heterogeneous Human Teams for Collaborative Decision Processes. 830-843 - Xiyuan Zhang, Daniel Ochoa, Regina Talonia, Jorge Poveda:
Deep Source-Seekers with Obstacle Avoidance: Adaptive Hybrid Control with Transformers In-The-Loop. 844-855 - Sean Anderson, João Pedro Hespanha:
Learning with contextual information in non-stationary environments. 856-868 - Leonard Jung, Alexander Estornell, Michael Everett:
Contingency Constrained Planning with MPPI within MPPI. 869-880 - Zhuoyu Xiao, Uday V. Shanbhag:
Computing Quasi-Nash Equilibria via Gradient-Response Schemes. 881-893 - Cevahir Köprülü, Po-han Li, Tianyu Qiu, Ruihan Zhao, Tyler Westenbroek, David Fridovich-Keil, Sandeep Chinchali, Ufuk Topcu:
Dense Dynamics-Aware Reward Synthesis: Integrating Prior Experience with Demonstrations. 894-906 - Tesshu Fujinami, Bruce D. Lee, Nikolai Matni, George J. Pappas:
Domain Randomization is Sample Efficient for Linear Quadratic Control. 907-919 - Ali Baheri, Zahra Shahrooei, Chirayu Salgarkar:
WAVE: Wasserstein Adaptive Value Estimation for Actor-Critic Reinforcement Learning. 920-931 - Kyungmin Kim, Davide Corsi, Andoni Rodríguez, JB Lanier, Benjami Parellada, Pierre Baldi, César Sánchez, Roy Fox:
Realizable Continuous-Space Shields for Safe Reinforcement Learning. 932-945 - Srikar Gouru, Siddharth Lakkoju, Rohan Chandra:
LiveNet: Robust, Minimally Invasive Multi-Robot Control for Safe and Live Navigation in Constrained Environments. 946-958 - Dvij Kalaria, Chinmay Maheshwari, Shankar Sastry:
α-RACER: Real-Time Algorithm for Game-Theoretic Motion Planning and Control in Autonomous Racing using Near-Potential Function. 959-972 - Damola Ajeyemi, Saber Jafarpour, Emiliano Dall'Anese:
Neural Network-assisted Interval Reachability for Systems with Control Barrier Function-Based Safe Controllers. 973-986 - Marcin Paluch, Florian Bolli, Pehuen Moure, Xiang Deng, Tobi Delbruck:
A-NC: Adaptive Neural Control with implicit online inference of privileged parameters. 987-998 - Nikolaos Bousias, Stefanos Pertigkiozoglou, Kostas Daniilidis, George J. Pappas:
Symmetries-enhanced Multi-Agent Reinforcement Learning. 999-1011 - Ahmad Al-Tawaha, Javad Lavaei, Ming Jin:
A Dynamic Penalization Framework for Online Rank-1 Semidefinite Programming Relaxations. 1012-1024 - Sunbochen Tang, Haoyuan Sun, Navid Azizan:
Meta-Learning for Adaptive Control with Automated Mirror Descent. 1025-1037 - Petar Bevanda, Nicolas Hoischen, Tobias Wittmann, Jan Brüdigam, Sandra Hirche, Boris Houska:
Kernel-Based Optimal Control: An Infinitesimal Generator Approach. 1038-1052 - Yangge Li, Chenxi Ji, Jai Anchalia, Yixuan Jia, Benjamin C. Yang, Daniel Zhuang, Sayan Mitra:
Lyapunov Perception Contracts for Operating Design Domains. 1053-1065 - Ruiyang Wang, Bowen He, Miroslav Pajic:
Neuro-Symbolic Deadlock Resolution in Multi-Robot Systems. 1066-1077 - Saptarshi Mandal, Xiaojun Lin, Rayadurgam Srikant:
A Theoretical Analysis of Soft-Label vs Hard-Label Training in Neural Networks. 1078-1089 - Alan Williams, Christopher Leon, Alexander Scheinker:
QP Based Constrained Optimization for Reliable PINN Training. 1090-1101 - Shuo Yang, Hongrui Zheng, Cristian-Ioan Vasile, George J. Pappas, Rahul Mangharam:
STLGame: Signal Temporal Logic Games in Adversarial Multi-Agent Systems. 1102-1114 - Taehyeun Kim, Anouck Girard, Ilya V. Kolmanovsky:
CIKAN: Constraint Informed Kolmogorov-Arnold Networks for Autonomous Spacecraft Rendezvous using Time Shift Governor. 1115-1126 - Zhexuan Zeng, Ruikun Zhou, Yiming Meng, Jun Liu:
Data-driven optimal control of unknown nonlinear dynamical systems using the Koopman operator. 1127-1139 - Haonan He, Yuheng Qiu, Junyi Geng:
Imperative MPC: An End-to-End Self-Supervised Learning with Differentiable MPC for UAV Attitude Control. 1140-1153 - Azra Begzadic, Nikhil Shinde, Sander Tonkens, Dylan Hirsch, Kaleb Ugalde, Michael C. Yip, Jorge Cortés, Sylvia L. Herbert:
Back to Base: Towards Hands-Off Learning via Safe Resets with Reach-Avoid Safety Filters. 1154-1166 - Behrad Samari, Mahdieh Zaker, Abolfazl Lavaei:
Abstraction-Based Control of Unknown Continuous-Space Models with Just Two Trajectories. 1167-1179 - Muhammad Qasim Elahi, Somtochukwu Oguchienti, Maheed H. Ahmed, Mahsa Ghasemi:
Reinforcement Learning from Multi-level and Episodic Human Feedback. 1180-1193 - Noel Brindise, Vijeth Hebbar, Riya Shah, Cedric Langbort:
"What are my options?"€: Explaining RL Agents with Diverse Near-Optimal Alternatives. 1194-1205 - Mishal Assif P. K, Yuliy Baryshnikov:
Topological State Space Inference for Dynamical Systems. 1206-1216 - Keyan Miao, Liqun Zhao, Han Wang, Konstantinos Gatsis, Antonis Papachristodoulou:
Opt-ODENet: Neural ODE Controller Design with Differentiable Optimization Layers for Safety and Stability. 1217-1229 - Peilun Li, Kaiyuan Tan, Thomas Beckers:
NAPI-MPC: Neural Accelerated Physics-Informed MPC for Nonlinear PDE Systems. 1230-1242 - Shubh Maheshwari, Anwesh Mohanty, Yadi Cao, Swithin Razu, Andrew McCulloch, Rose Yu:
BIGE : Biomechanics-informed GenAI for Exercise Science. 1243-1256 - Michael Lu, Jashanraj Gosain, Luna Sang, Mo Chen:
Safe Learning in the Real World via Adaptive Shielding with Hamilton-Jacobi Reachability. 1257-1270 - Yahya Sattar, Yassir Jedra, Maryam Fazel, Sarah Dean:
Finite Sample Identification of Partially Observed Bilinear Dynamical Systems. 1271-1285 - Uday Kiran Reddy Tadipatri, Benjamin D. Haeffele, Joshua Agterberg, Ingvar M. Ziemann, René Vidal:
Nonconvex Linear System Identification with Minimal State Representation. 1286-1299 - Hsin-Jung Yang, Mahsa Khosravi, Benjamin Walt, Girish Krishnan, Soumik Sarkar:
Zero-shot Sim-to-Real Transfer for Reinforcement Learning-based Visual Servoing of Soft Continuum Arms. 1300-1312 - Maryann Rui, Munther A. Dahleh:
Finite Sample Analysis of Tensor Decomposition for Learning Mixtures of Linear Systems. 1313-1325 - Pedram Rabiee, Amirsaeid Safari:
Safe Exploration in Reinforcement Learning: Training Backup Control Barrier Functions with Zero Training-Time Safety Violations. 1326-1337 - Evangelos Chatzipantazis, Nishanth Rao, Kostas Daniilidis:
STRiDE: STate-space Riemannian Diffusion for Equivariant Planning. 1338-1352 - Hao-Lun Hsu, Miroslav Pajic:
Safe Cooperative Multi-Agent Reinforcement Learning with Function Approximation. 1353-1364 - Hanna Krasowski, Eric Palanques-Tost, Calin Belta, Murat Arcak:
Learning Biomolecular Models using Signal Temporal Logic. 1365-1377 - Shahbaz P. Qadri Syed, He Bai:
Exploiting inter-agent coupling information for efficient reinforcement learning of cooperative LQR. 1378-1391 - Fengze Xie, Sizhe Wei, Yue Song, Yisong Yue, Lu Gan:
Morphological-Symmetry-Equivariant Heterogeneous Graph Neural Network for Robotic Dynamics Learning. 1392-1405 - Minah Lee, Uday Kamal, Saibal Mukhopadhyay:
Learning Collective Dynamics of Multi-Agent Systems using Event-based Vision. 1406-1418 - Seyed Yousef Soltanian, Wenlong Zhang:
PACE: A Framework for Learning and Control in Linear Incomplete-Information Differential Games. 1419-1433 - Jörn Tebbe, Andreas Besginow, Markus Lange-Hegermann:
Physics-informed Gaussian Processes as Linear Model Predictive Controller. 1434-1446 - Haoyu Li, Xiangru Zhong, Bin Hu, Huan Zhang:
Neural Contraction Metrics with Formal Guarantees for Discrete-Time Nonlinear Dynamical Systems. 1447-1459 - Negar Monir, Mahdieh Sadat Sadabadi, Sadegh Soudjani:
Robust Control of Uncertain Switched Affine Systems via Scenario Optimization. 1460-1471 - Zhiyu An, Zhibo Hou, Wan Du:
Disentangling Uncertainties by Learning Compressed Data Representation. 1472-1483 - Gokul Puthumanaillam, Jae Hyuk Song, Nurzhan Yesmagambet, Shinkyu Park, Melkior Ornik:
TAB-Fields: A Maximum Entropy Framework for Mission-Aware Adversarial Planning. 1484-1497 - Yichao Zhong, Chong Zhang, Tairan He, Guanya Shi:
Bridging Adaptivity and Safety: Learning Agile Collision-Free Locomotion Across Varied Physics. 1498-1511 - Ilayda Canyakmaz, Iosif Sakos, Wayne Lin, Antonios Varvitsiotis, Georgios Piliouras:
Learning and steering game dynamics towards desirable outcomes. 1512-1524 - Haokun Yu, Jingyuan Zhou, Kaidi Yang:
Interaction-Aware Parameter Privacy-Preserving Data Sharing in Coupled Systems via Particle Filter Reinforcement Learning. 1525-1536 - Ibon Gracia, Luca Laurenti, Manuel Mazo Jr., Alessandro Abate, Morteza Lahijanian:
Temporal Logic Control for Nonlinear Stochastic Systems Under Unknown Disturbances. 1537-1549 - Mahdi Nazeri, Thom Badings, Sadegh Soudjani, Alessandro Abate:
Data-Driven Yet Formal Policy Synthesis for Stochastic Nonlinear Dynamical Systems. 1550-1564 - Mohamed Abou-Taleb, Maximilian Raff, Kathrin Flaßkamp, C. David Remy:
Koopman Based Trajectory Optimization with Mixed Boundaries. 1565-1577
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