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Editors: Nikolai Matni, Manfred Morari, George J. Pappas
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Learning on Manifolds: Universal Approximations Properties using Geometric Controllability Conditions for Neural ODEs
; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1-11
Interval Reachability of Nonlinear Dynamical Systems with Neural Network Controllers
Saber Jafarpour, Akash Harapanahalli, Samuel Coogan; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:12-25
Physics-Informed Model-Based Reinforcement Learning
Adithya Ramesh, Balaraman Ravindran; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:26-37
Learning-to-Learn to Guide Random Search: Derivative-Free Meta Blackbox Optimization on Manifold
Bilgehan Sel, Ahmad Tawaha, Yuhao Ding, Ruoxi Jia, Bo Ji, Javad Lavaei, Ming Jin; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:38-50
Can Direct Latent Model Learning Solve Linear Quadratic Gaussian Control?
Yi Tian, Kaiqing Zhang, Russ Tedrake, Suvrit Sra; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:51-63
Policy Learning for Active Target Tracking over Continuous $SE(3)$ Trajectories
Pengzhi Yang, Shumon Koga, Arash Asgharivaskasi, Nikolay Atanasov; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:64-75
Guaranteed Conformance of Neurosymbolic Models to Natural Constraints
Kaustubh Sridhar, Souradeep Dutta, James Weimer, Insup Lee; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:76-89
ISAACS: Iterative Soft Adversarial Actor-Critic for Safety
Kai-Chieh Hsu, Duy Phuong Nguyen, Jaime Fernàndez Fisac; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:90-103
Safe and Efficient Reinforcement Learning using Disturbance-Observer-Based Control Barrier Functions
Yikun Cheng, Pan Zhao, Naira Hovakimyan; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:104-115
Learning the dynamics of autonomous nonlinear delay systems
Xunbi Ji, Gabor Orosz; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:116-127
Improving Gradient Computation for Differentiable Physics Simulation with Contacts
Yaofeng Desmond Zhong, Jiequn Han, Biswadip Dey, Georgia Olympia Brikis; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:128-141
Learning Trust Over Directed Graphs in Multiagent Systems
Orhan Eren Akgun, Arif Kerem Dayi, Stephanie Gil, Angelia Nedich; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:142-154
Contrastive Example-Based Control
Kyle Beltran Hatch, Benjamin Eysenbach, Rafael Rafailov, Tianhe Yu, Ruslan Salakhutdinov, Sergey Levine, Chelsea Finn; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:155-169
DiffTune$^+$: Hyperparameter-Free Auto-Tuning using Auto-Differentiation
Sheng Cheng, Lin Song, Minkyung Kim, Shenlong Wang, Naira Hovakimyan; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:170-183
Policy Gradient Play with Networked Agents in Markov Potential Games
Sarper Aydin, Ceyhun Eksin; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:184-195
Sample Complexity Bound for Evaluating the Robust Observer’s Performance under Coprime Factors Uncertainty
Serban Sabau, Yifei Zhang, Sourav Kumar Ukil; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:196-207
Learning Robust State Observers using Neural ODEs
Keyan Miao, Konstantinos Gatsis; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:208-219
End-to-End Learning to Warm-Start for Real-Time Quadratic Optimization
Rajiv Sambharya, Georgina Hall, Brandon Amos, Bartolomeo Stellato; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:220-234
Full Gradient Deep Reinforcement Learning for Average-Reward Criterion
Tejas Pagare, Vivek Borkar, Konstantin Avrachenkov; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:235-247
Regret Analysis of Online LQR Control via Trajectory Prediction and Tracking
Yitian Chen, Timothy L Molloy, Tyler Summers, Iman Shames; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:248-258
Learning Policy-Aware Models for Model-Based Reinforcement Learning via Transition Occupancy Matching
Yecheng Jason Ma, Kausik Sivakumar, Jason Yan, Osbert Bastani, Dinesh Jayaraman; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:259-271
Compositional Neural Certificates for Networked Dynamical Systems
Songyuan Zhang, Yumeng Xiu, Guannan Qu, Chuchu Fan; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:272-285
In-Distribution Barrier Functions: Self-Supervised Policy Filters that Avoid Out-of-Distribution States
Fernando Castañeda, Haruki Nishimura, Rowan Thomas McAllister, Koushil Sreenath, Adrien Gaidon; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:286-299
Adaptive Conformal Prediction for Motion Planning among Dynamic Agents
Anushri Dixit, Lars Lindemann, Skylar X Wei, Matthew Cleaveland, George J. Pappas, Joel W. Burdick; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:300-314
Provably Efficient Generalized Lagrangian Policy Optimization for Safe Multi-Agent Reinforcement Learning
Dongsheng Ding, Xiaohan Wei, Zhuoran Yang, Zhaoran Wang, Mihailo Jovanovic; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:315-332
Equilibria of Fully Decentralized Learning in Networked Systems
Yan Jiang, Wenqi Cui, Baosen Zhang, Jorge Cortes; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:333-345
Operator Learning for Nonlinear Adaptive Control
Luke Bhan, Yuanyuan Shi, Miroslav Krstic; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:346-357
A Generalizable Physics-informed Learning Framework for Risk Probability Estimation
Zhuoyuan Wang, Yorie Nakahira; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:358-370
Efficient Reinforcement Learning Through Trajectory Generation
Wenqi Cui, Linbin Huang, Weiwei Yang, Baosen Zhang; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:371-382
Concentration Phenomenon for Random Dynamical Systems: An Operator Theoretic Approach
Muhammad Abdullah Naeem; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:383-394
Modified Policy Iteration for Exponential Cost Risk Sensitive MDPs
Yashaswini Murthy, Mehrdad Moharrami, R. Srikant; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:395-406
Automated Reachability Analysis of Neural Network-Controlled Systems via Adaptive Polytopes
Taha Entesari, Mahyar Fazlyab; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:407-419
Designing System Level Synthesis Controllers for Nonlinear Systems with Stability Guarantees
Lauren E Conger, Sydney Vernon, Eric Mazumdar; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:420-430
Targeted Adversarial Attacks against Neural Network Trajectory Predictors
Kaiyuan Tan, Jun Wang, Yiannis Kantaros; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:431-444
Can Learning Deteriorate Control? Analyzing Computational Delays in Gaussian Process-Based Event-Triggered Online Learning
Xiaobing Dai, Armin Lederer, Zewen Yang, Sandra Hirche; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:445-457
Probabilistic Invariance for Gaussian Process State Space Models
Paul Griffioen, Alex Devonport, Murat Arcak; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:458-468
Compositional Learning-based Planning for Vision POMDPs
Sampada Deglurkar, Michael H Lim, Johnathan Tucker, Zachary N Sunberg, Aleksandra Faust, Claire Tomlin; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:469-482
Certified Invertibility in Neural Networks via Mixed-Integer Programming
Tianqi Cui, Thomas Bertalan, George J. Pappas, Manfred Morari, Yannis Kevrekidis, Mahyar Fazlyab; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:483-496
The Impact of the Geometric Properties of the Constraint Set in Safe Optimization with Bandit Feedback
Spencer Hutchinson, Berkay Turan, Mahnoosh Alizadeh; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:497-508
Template-Based Piecewise Affine Regression
Guillaume O Berger, Sriram Sankaranarayanan; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:509-520
Physics-enhanced Gaussian Process Variational Autoencoder
Thomas Beckers, Qirui Wu, George J. Pappas; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:521-533
A Reinforcement Learning Look at Risk-Sensitive Linear Quadratic Gaussian Control
Leilei Cui, Tamer Basar, Zhong-Ping Jiang; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:534-546
Time-Incremental Learning of Temporal Logic Classifiers Using Decision Trees
Erfan Aasi, Mingyu Cai, Cristian Ioan Vasile, Calin Belta; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:547-559
Adaptive Regret for Control of Time-Varying Dynamics
Paula Gradu, Elad Hazan, Edgar Minasyan; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:560-572
Automatic Integration for Fast and Interpretable Neural Point Processes
Zihao Zhou, Rose Yu; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:573-585
Multi-Task Imitation Learning for Linear Dynamical Systems
Thomas T. Zhang, Katie Kang, Bruce D Lee, Claire Tomlin, Sergey Levine, Stephen Tu, Nikolai Matni; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:586-599
Accelerating Trajectory Generation for Quadrotors Using Transformers
Srinath Tankasala, Mitch Pryor; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:600-611
A finite-sample analysis of multi-step temporal difference estimates
Yaqi Duan, Martin J. Wainwright; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:612-624
Practical Critic Gradient based Actor Critic for On-Policy Reinforcement Learning
Swaminathan Gurumurthy, Zachary Manchester, J Zico Kolter; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:625-638
Deep Off-Policy Iterative Learning Control
Swaminathan Gurumurthy, J Zico Kolter, Zachary Manchester; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:639-652
Transportation-Inequalities, Lyapunov Stability and Sampling for Dynamical Systems on Continuous State Space
Muhammad Abdullah Naeem, Miroslav Pajic; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:653-664
Learning Disturbances Online for Risk-Aware Control: Risk-Aware Flight with Less Than One Minute of Data
Prithvi Akella, Skylar X Wei, Joel W. Burdick, Aaron Ames; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:665-678
Compositional Learning of Dynamical System Models Using Port-Hamiltonian Neural Networks
Cyrus Neary, Ufuk Topcu; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:679-691
Multi-Agent Reinforcement Learning with Reward Delays
Yuyang Zhang, Runyu Zhang, Yuantao Gu, Na Li; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:692-704
CatlNet: Learning Communication and Coordination Policies from CaTL+ Specifications
Wenliang Liu, Kevin Leahy, Zachary Serlin, Calin Belta; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:705-717
Roll-Drop: accounting for observation noise with a single parameter
Luigi Campanaro, Daniele De Martini, Siddhant Gangapurwala, Wolfgang Merkt, Ioannis Havoutis; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:718-730
Lie Group Forced Variational Integrator Networks for Learning and Control of Robot Systems
Valentin Duruisseaux, Thai P. Duong, Melvin Leok, Nikolay Atanasov; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:731-744
Learning Object-Centric Dynamic Modes from Video and Emerging Properties
Armand Comas, Christian Fernandez Lopez, Sandesh Ghimire, Haolin Li, Mario Sznaier, Octavia Camps; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:745-769
Continuous Versatile Jumping Using Learned Action Residuals
Yuxiang Yang, Xiangyun Meng, Wenhao Yu, Tingnan Zhang, Jie Tan, Byron Boots; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:770-782
Probabilistic Safeguard for Reinforcement Learning Using Safety Index Guided Gaussian Process Models
Weiye Zhao, Tairan He, Changliu Liu; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:783-796
Hierarchical Policy Blending As Optimal Transport
An Thai Le, Kay Hansel, Jan Peters, Georgia Chalvatzaki; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:797-812
Top-k data selection via distributed sample quantile inference
Xu Zhang, Marcos M. Vasconcelos; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:813-824
Model-based Validation as Probabilistic Inference
Harrison Delecki, Anthony Corso, Mykel Kochenderfer; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:825-837
Nonlinear Controllability and Function Representation by Neural Stochastic Differential Equations
Tanya Veeravalli, Maxim Raginsky; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:838-850
Agile Catching with Whole-Body MPC and Blackbox Policy Learning
Saminda Abeyruwan, Alex Bewley, Nicholas Matthew Boffi, Krzysztof Marcin Choromanski, David B D’Ambrosio, Deepali Jain, Pannag R Sanketi, Anish Shankar, Vikas Sindhwani, Sumeet Singh, Jean-Jacques Slotine, Stephen Tu; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:851-863
Distributionally Robust Lyapunov Function Search Under Uncertainty
Kehan Long, Yinzhuang Yi, Jorge Cortes, Nikolay Atanasov; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:864-877
Black-Box vs. Gray-Box: A Case Study on Learning Table Tennis Ball Trajectory Prediction with Spin and Impacts
Jan Achterhold, Philip Tobuschat, Hao Ma, Dieter Büchler, Michael Muehlebach, Joerg Stueckler; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:878-890
Data-driven memory-dependent abstractions of dynamical systems
Adrien Banse, Licio Romao, Alessandro Abate, Raphael Jungers; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:891-902
Congestion Control of Vehicle Traffic Networks by Learning Structural and Temporal Patterns
SooJean Han, Soon-Jo Chung, Johanna Gustafson; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:903-914
A Learning and Control Perspective for Microfinance
Xiyu Deng, Christian Kurniawan, Adhiraj Chakraborty, Assane Gueye, Niangjun Chen, Yorie Nakahira; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:915-927
Physics-Guided Active Learning of Environmental Flow Fields
Reza Khodayi-mehr, Pingcheng Jian, Michael M. Zavlanos; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:928-940
CT-DQN: Control-Tutored Deep Reinforcement Learning
Francesco De Lellis, Marco Coraggio, Giovanni Russo, Mirco Musolesi, Mario di Bernardo; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:941-953
Failing with Grace: Learning Neural Network Controllers that are Boundedly Unsafe
Panagiotis Vlantis, Leila Bridgeman, Michael Zavlanos; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:954-965
Probabilistic Verification of ReLU Neural Networks via Characteristic Functions
Joshua Pilipovsky, Vignesh Sivaramakrishnan, Meeko Oishi, Panagiotis Tsiotras; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:966-979
Data-driven Stochastic Output-Feedback Predictive Control: Recursive Feasibility through Interpolated Initial Conditions
Guanru Pan, Ruchuan Ou, Timm Faulwasser; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:980-992
Detection of Man-in-the-Middle Attacks in Model-Free Reinforcement Learning
Rishi Rani, Massimo Franceschetti; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:993-1007
On Controller Reduction in Linear Quadratic Gaussian Control with Performance Bounds
Zhaolin Ren, Yang Zheng, Maryam Fazel, Na Li; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1008-1019
Competing Bandits in Time Varying Matching Markets
Deepan Muthirayan, Chinmay Maheshwari, Pramod Khargonekar, Shankar Sastry; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1020-1031
Regret Guarantees for Online Deep Control
Xinyi Chen, Edgar Minasyan, Jason D. Lee, Elad Hazan; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1032-1045
Frequency Domain Gaussian Process Models for $H^∞$ Uncertainties
Alex Devonport, Peter Seiler, Murat Arcak; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1046-1057
Satellite Navigation and Coordination with Limited Information Sharing
Sydney Dolan, Siddharth Nayak, Hamsa Balakrishnan; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1058-1071
Toward Multi-Agent Reinforcement Learning for Distributed Event-Triggered Control
Lukas Kesper, Sebastian Trimpe, Dominik Baumann; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1072-1085
Analysis and Detectability of Offline Data Poisoning Attacks on Linear Dynamical Systems
Alessio Russo; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1086-1098
Learning Stability Attention in Vision-based End-to-end Driving Policies
Tsun-Hsuan Wang, Wei Xiao, Makram Chahine, Alexander Amini, Ramin Hasani, Daniela Rus; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1099-1111
Provably Efficient Model-free RL in Leader-Follower MDP with Linear Function Approximation
Arnob Ghosh; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1112-1124
Learning-enhanced Nonlinear Model Predictive Control using Knowledge-based Neural Ordinary Differential Equations and Deep Ensembles
Kong Yao Chee, M. Ani Hsieh, Nikolai Matni; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1125-1137
Online switching control with stability and regret guarantees
Yingying Li, James A Preiss, Na Li, Yiheng Lin, Adam Wierman, Jeff S Shamma; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1138-1151
CLAS: Coordinating Multi-Robot Manipulation with Central Latent Action Spaces
Elie Aljalbout, Maximilian Karl, Patrick van der Smagt; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1152-1166
Learning Coherent Clusters in Weakly-Connected Network Systems
Hancheng Min, Enrique Mallada; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1167-1179
Predictive safety filter using system level synthesis
Antoine Leeman, Johannes Köhler, Samir Bennani, Melanie Zeilinger; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1180-1192
Time Dependent Inverse Optimal Control using Trigonometric Basis Functions
Rahel Rickenbach, Elena Arcari, Melanie Zeilinger; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1193-1204
Interpreting Primal-Dual Algorithms for Constrained Multiagent Reinforcement Learning
Daniel Tabas, Ahmed S Zamzam, Baosen Zhang; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1205-1217
Learning Locomotion Skills from MPC in Sensor Space
Majid Khadiv, Avadesh Meduri, Huaijiang Zhu, Ludovic Righetti, Bernhard Schölkopf; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1218-1230
Probabilistic Symmetry for Multi-Agent Dynamics
Sophia Huiwen Sun, Robin Walters, Jinxi Li, Rose Yu; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1231-1244
Policy Evaluation in Distributional LQR
Zifan Wang, Yulong Gao, Siyi Wang, Michael M. Zavlanos, Alessandro Abate, Karl Henrik Johansson; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1245-1256
Reachability Analysis-based Safety-Critical Control using Online Fixed-Time Reinforcement Learning
Nick-Marios Kokolakis, Kyriakos G Vamvoudakis, Wassim Haddad; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1257-1270
Online Estimation of the Koopman Operator Using Fourier Features
Tahiya Salam, Alice Kate Li, M. Ani Hsieh; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1271-1283
Hybrid Multi-agent Deep Reinforcement Learning for Autonomous Mobility on Demand Systems
Tobias Enders, James Harrison, Marco Pavone, Maximilian Schiffer; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1284-1296
Model-Based Reinforcement Learning for Cavity Filter Tuning
Doumitrou Daniil Nimara, Mohammadreza Malek-Mohammadi, Petter Ogren, Jieqiang Wei, Vincent Huang; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1297-1307
FedSysID: A Federated Approach to Sample-Efficient System Identification
Han Wang, Leonardo Felipe Toso, James Anderson; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1308-1320
Lipschitz constant estimation for 1D convolutional neural networks
Patricia Pauli, Dennis Gramlich, Frank Allgöwer; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1321-1332
Rectified Pessimistic-Optimistic Learning for Stochastic Continuum-armed Bandit with Constraints
Hengquan Guo, Zhu Qi, Xin Liu; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1333-1344
Best of Both Worlds in Online Control: Competitive Ratio and Policy Regret
Gautam Goel, Naman Agarwal, Karan Singh, Elad Hazan; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1345-1356
Offline Model-Based Reinforcement Learning for Tokamak Control
Ian Char, Joseph Abbate, Laszlo Bardoczi, Mark Boyer, Youngseog Chung, Rory Conlin, Keith Erickson, Viraj Mehta, Nathan Richner, Egemen Kolemen, Jeff Schneider; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1357-1372
A Dynamical Systems Perspective on Discrete Optimization
Tong Guanchun, Michael Muehlebach; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1373-1386
Linear Stochastic Bandits over a Bit-Constrained Channel
Aritra Mitra, Hamed Hassani, George J. Pappas; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1387-1399
Hybrid Systems Neural Control with Region-of-Attraction Planner
Yue Meng, Chuchu Fan; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1400-1415
Online Saddle Point Tracking with Decision-Dependent Data
Killian Reed Wood, Emiliano Dall’Anese; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1416-1428
Wing shape estimation with Extended Kalman filtering and KalmanNet neural network of a flexible wing aircraft
Bence Zsombor Hadlaczky, Noémi Friedman, Béla Takarics, Balint Vanek; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1429-1440
Filter-Aware Model-Predictive Control
Baris Kayalibay, Atanas Mirchev, Ahmed Agha, Patrick van der Smagt, Justin Bayer; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1441-1454
Hyperparameter Tuning of an Off-Policy Reinforcement Learning Algorithm for H∞ Tracking Control
Alireza Farahmandi, Brian C Reitz, Mark Debord, Douglas Philbrick, Katia Estabridis, Gary Hewer; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1455-1466
DLKoopman: A deep learning software package for Koopman theory
Sourya Dey, Eric William Davis; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1467-1479
Benchmarking Rigid Body Contact Models
Michelle Guo, Yifeng Jiang, Andrew Everett Spielberg, Jiajun Wu, Karen Liu; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1480-1492
Model Predictive Control via On-Policy Imitation Learning
Kwangjun Ahn, Zakaria Mhammedi, Horia Mania, Zhang-Wei Hong, Ali Jadbabaie; Proceedings of The 5th Annual Learning for Dynamics and Control Conference, PMLR 211:1493-1505
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