L4DC

Publications

2024

Berkay Turan, Spencer Hutchinson, Mahnoosh Alizadeh
Safe dynamic pricing for nonstationary network resource allocation. L4DC (2024)
Chenguang Zhao, Huan Yu
Learning "Look-Ahead" Nonlocal Traffic Dynamics in a Ring Road. L4DC (2024)
Amon Lahr, Filip Tronarp, Nathanael Bosch, Jonathan Schmidt, Philipp Hennig, Melanie N. Zeilinger
Probabilistic ODE solvers for integration error-aware numerical optimal control. L4DC (2024)
Tim Salzmann, Jon Arrizabalaga, Joel Andersson, Marco Pavone, Markus Ryll
Learning for CasADi: Data-driven models in numerical optimization. L4DC (2024)
Bruce D. Lee, Anders Rantzer, Nikolai Matni
Nonasymptotic regret analysis of adaptive linear quadratic control with model misspecification. L4DC (2024)
Riccardo Brumali, Guido Carnevale, Giuseppe Notarstefano
A deep learning approach for distributed aggregative optimization with users' feedback. L4DC (2024)
Anders Rantzer
A data-driven Riccati equation. L4DC (2024)
Puya Latafat, Andreas Themelis, Panagiotis Patrinos
On the convergence of adaptive first order methods: proximal gradient and alternating minimization algorithms. L4DC (2024)
Nolan Fey, He Li, Nicholas Adrian, Patrick M. Wensing, Michael D. Lemmon
A learning-based framework to adapt legged robots on-the-fly to unexpected disturbances. L4DC (2024)
Mohamad Louai Shehab, Antoine Aspeel, Nikos Aréchiga, Andrew Best, Necmiye Ozay
Learning true objectives: Linear algebraic characterizations of identifiability in inverse reinforcement learning. L4DC (2024)
Abdullah Akgül, Gozde Unal, Melih Kandemir
Continual learning of multi-modal dynamics with external memory. L4DC (2024)
Beomseok Kang, Harshit Kumar, Minah Lee, Biswadeep Chakraborty, Saibal Mukhopadhyay
Learning locally interacting discrete dynamical systems: Towards data-efficient and scalable prediction. L4DC (2024)
Daniel Jarne Ornia, Licio Romao, Lewis Hammond, Manuel Mazo Jr., Alessandro Abate
Bounded robustness in reinforcement learning via lexicographic objectives. L4DC (2024)
Charis J. Stamouli, Lars Lindemann, George J. Pappas
Recursively feasible shrinking-horizon MPC in dynamic environments with conformal prediction guarantees. L4DC (2024)
Yukai Tang, Jean-Bernard Lasserre, Heng Yang
Uncertainty quantification of set-membership estimation in control and perception: Revisiting the minimum enclosing ellipsoid. L4DC (2024)
Yuliang Gu, Sheng Cheng, Naira Hovakimyan
Proto-MPC: An encoder-prototype-decoder approach for quadrotor control in challenging winds. L4DC (2024)
Hemant Kumawat, Biswadeep Chakraborty, Saibal Mukhopadhyay
STEMFold: Stochastic temporal manifold for multi-agent interactions in the presence of hidden agents. L4DC (2024)
Mohammad Alsalti, Victor G. Lopez, Matthias Albrecht Müller
An efficient data-based off-policy Q-learning algorithm for optimal output feedback control of linear systems. L4DC (2024)
Jannis O. Lübsen, Christian Hespe, Annika Eichler
Towards safe multi-task Bayesian optimization. L4DC (2024)
Noel Brindise, Andres Felipe Posada-Moreno, Cedric Langbort, Sebastian Trimpe
Pointwise-in-time diagnostics for reinforcement learning during training and runtime. L4DC (2024)
Kimia Kazemian, Yahya Sattar, Sarah Dean
Random features approximation for control-affine systems. L4DC (2024)
Amy K. Strong, Leila Jasmine Bridgeman
Data driven verification of positive invariant sets for discrete, nonlinear systems. L4DC (2024)
Yitao Bai, Thinh T. Doan
Finite-time complexity of incremental policy gradient methods for solving multi-task reinforcement learning. L4DC (2024)
Xiangyuan Zhang, Weichao Mao, Saviz Mowlavi, Mouhacine Benosman, Tamer Basar
Controlgym: Large-scale control environments for benchmarking reinforcement learning algorithms. L4DC (2024)
Jaeuk Shin, Giho Kim, Howon Lee, Joonho Han, Insoon Yang
On task-relevant loss functions in meta-reinforcement learning. L4DC (2024)
Zeji Yi, Chaoyi Pan, Guanqi He, Guannan Qu, Guanya Shi
CoVO-MPC: Theoretical analysis of sampling-based MPC and optimal covariance design. L4DC (2024)
Tara Toufighi, Minh Bui, Rakesh Shrestha, Mo Chen
Decision boundary learning for safe vision-based navigation via Hamilton-Jacobi reachability analysis and support vector machine. L4DC (2024)
Heiko Hoppe, Tobias Enders, Quentin Cappart, Maximilian Schiffer
Global rewards in multi-agent deep reinforcement learning for autonomous mobility on demand systems. L4DC (2024)
Mohak Bhardwaj, Thomas Lampe, Michael Neunert, Francesco Romano, Abbas Abdolmaleki, Arunkumar Byravan, Markus Wulfmeier, Martin A. Riedmiller, Jonas Buchli
Real-world fluid directed rigid body control via deep reinforcement learning. L4DC (2024)
Emma Clark, Kanghyun Ryu, Negar Mehr
Adaptive teaching in heterogeneous agents: Balancing surprise in sparse reward scenarios. L4DC (2024)
Johan Peralez, Madiha Nadri
Deep model-free KKL observer: A switching approach. L4DC (2024)
Hao-Lun Hsu, Miroslav Pajic
Robust exploration with adversary via Langevin Monte Carlo. L4DC (2024)
Christine Allen-Blanchette
Hamiltonian GAN. L4DC (2024)
Zetong Xuan, Alper Kamil Bozkurt, Miroslav Pajic, Yu Wang
On the uniqueness of solution for the Bellman equation of LTL objectives. L4DC (2024)
Patrick Henkel, Tobias Kasperski, Phillip Stoffel, Dirk Müller
Interpretable data-driven model predictive control of building energy systems using SHAP. L4DC (2024)
Giulio Giacomuzzo, Riccardo Cescon, Diego Romeres, Ruggero Carli, Alberto Dalla Libera
Lagrangian inspired polynomial estimator for black-box learning and control of underactuated systems. L4DC (2024)
Weichao Mao, Haoran Qiu, Chen Wang, Hubertus Franke, Zbigniew Kalbarczyk, Tamer Basar
$\widetilde{O}(T^{-1})$ {C}onvergence to (coarse) correlated equilibria in full-information general-sum markov games. L4DC (2024)
Rui Yan, Gabriel Santos, Gethin Norman, David Parker, Marta Kwiatkowska
HSVI-based online minimax strategies for partially observable stochastic games with neural perception mechanisms. L4DC (2024)
Emma Cramer, Jonas Reiher, Sebastian Trimpe
Tracking object positions in reinforcement learning: A metric for keypoint detection. L4DC (2024)
Songyuan Zhang, Chuchu Fan
Learning to stabilize high-dimensional unknown systems using Lyapunov-guided exploration. L4DC (2024)
Paula X. Chen, Tingwei Meng, Zongren Zou, Jérôme Darbon, George Em Karniadakis
Leveraging Hamilton-Jacobi PDEs with time-dependent Hamiltonians for continual scientific machine learning. L4DC (2024)
Dieter Teichrib, Moritz Schulze Darup
Piecewise regression via mixed-integer programming for MPC. L4DC (2024)
Ross Drummond, Chris Guiver, Matthew C. Turner
Convex neural network synthesis for robustness in the 1-norm. L4DC (2024)
Rahel Rickenbach, Anna Scampicchio, Melanie N. Zeilinger
Inverse optimal control as an errors-in-variables problem. L4DC (2024)
Yatong Bai, Brendon G. Anderson, Somayeh Sojoudi
Mixing classifiers to alleviate the accuracy-robustness trade-off. L4DC (2024)
Motoya Ohnishi, Iretiayo Akinola, Jie Xu, Ajay Mandlekar, Fabio Ramos
Signatures meet dynamic programming: Generalizing Bellman equations for trajectory following. L4DC (2024)
Sean Vaskov, Wilko Schwarting, Chris L. Baker
Do no harm: A counterfactual approach to safe reinforcement learning. L4DC (2024)
Zhenjiang Mao, Carson Sobolewski, Ivan Ruchkin
How safe am I given what I see? Calibrated prediction of safety chances for image-controlled autonomy. L4DC (2024)
Kaiyuan Tan, Peilun Li, Thomas Beckers
Physics-constrained learning for PDE systems with uncertainty quantified port-Hamiltonian models. L4DC (2024)

volume 242, 2024

6th Annual Learning for Dynamics & Control Conference, 15-17 July 2024, University of Oxford, Oxford, UK. L4DC 242 (2024)