[edit]
Volume 242: 6th Annual Learning for Dynamics & Control Conference, 15-17 July 2024, University of Oxford, Oxford, UK
[edit]
Editors: Alessandro Abate, Mark Cannon, Kostas Margellos, Antonis Papachristodoulou
Leveraging Hamilton-Jacobi PDEs with time-dependent Hamiltonians for continual scientific machine learning
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1-12
;[abs][Download PDF]
Data-efficient, explainable and safe box manipulation: Illustrating the advantages of physical priors in model-predictive control
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:13-24
;[abs][Download PDF]
Gradient shaping for multi-constraint safe reinforcement learning
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:25-39
;[abs][Download PDF]
Continual learning of multi-modal dynamics with external memory
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:40-51
;[abs][Download PDF]
Learning to stabilize high-dimensional unknown systems using Lyapunov-guided exploration
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:52-67
;[abs][Download PDF]
An investigation of time reversal symmetry in reinforcement learning
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:68-79
;[abs][Download PDF]
HSVI-based online minimax strategies for partially observable stochastic games with neural perception mechanisms
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:80-91
;[abs][Download PDF]
Real-time safe control of neural network dynamic models with sound approximation
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:92-103
;[abs][Download PDF]
Tracking object positions in reinforcement learning: A metric for keypoint detection
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:104-116
;[abs][Download PDF]
Linearised data-driven LSTM-based control of multi-input HVAC systems
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:117-129
;[abs][Download PDF]
The behavioral toolbox
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:130-141
;[abs][Download PDF]
Learning “look-ahead” nonlocal traffic dynamics in a ring road
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:142-154
;[abs][Download PDF]
Safe dynamic pricing for nonstationary network resource allocation
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:155-167
;[abs][Download PDF]
Safe online convex optimization with multi-point feedback
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:168-180
;[abs][Download PDF]
Controlgym: Large-scale control environments for benchmarking reinforcement learning algorithms
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:181-196
;[abs][Download PDF]
On the convergence of adaptive first order methods: Proximal gradient and alternating minimization algorithms
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:197-208
;[abs][Download PDF]
Strengthened stability analysis of discrete-time Lurie systems involving ReLU neural networks
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:209-221
;[abs][Download PDF]
Interpretable data-driven model predictive control of building energy systems using SHAP
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:222-234
;[abs][Download PDF]
Physics-informed Neural Networks with Unknown Measurement Noise
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:235-247
;[abs][Download PDF]
Adaptive online non-stochastic control
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:248-259
;[abs][Download PDF]
Global rewards in multi-agent deep reinforcement learning for autonomous mobility on demand systems
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:260-272
;[abs][Download PDF]
Soft convex quantization: revisiting Vector Quantization with convex optimization
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:273-285
;[abs][Download PDF]
Uncertainty quantification of set-membership estimation in control and perception: Revisiting the minimum enclosing ellipsoid
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:286-298
;[abs][Download PDF]
Minimax dual control with finite-dimensional information state
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:299-311
;[abs][Download PDF]
An efficient data-based off-policy Q-learning algorithm for optimal output feedback control of linear systems
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:312-323
;[abs][Download PDF]
Adapting image-based RL policies via predicted rewards
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:324-336
;[abs][Download PDF]
Piecewise regression via mixed-integer programming for MPC
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:337-348
;[abs][Download PDF]
Parameter-adaptive approximate MPC: Tuning neural-network controllers without retraining
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:349-360
;[abs][Download PDF]
$\widetilde{O}(T^{-1})$ Convergence to (coarse) correlated equilibria in full-information general-sum Markov games
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:361-374
;[abs][Download PDF]
Inverse optimal control as an errors-in-variables problem
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:375-386
;[abs][Download PDF]
Learning soft constrained MPC value functions: Efficient MPC design and implementation providing stability and safety guarantees
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:387-398
;[abs][Download PDF]
MPC-inspired reinforcement learning for verifiable model-free control
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:399-413
;[abs][Download PDF]
Real-world fluid directed rigid body control via deep reinforcement learning
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:414-427
;[abs][Download PDF]
On the uniqueness of solution for the Bellman equation of LTL objectives
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:428-439
;[abs][Download PDF]
Decision boundary learning for safe vision-based navigation via Hamilton-Jacobi reachability analysis and support vector machine
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:440-452
;[abs][Download PDF]
Understanding the difficulty of solving Cauchy problems with PINNs
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:453-465
;[abs][Download PDF]
Signatures meet dynamic programming: Generalizing Bellman equations for trajectory following
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:466-479
;[abs][Download PDF]
Online decision making with history-average dependent costs
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:480-491
;[abs][Download PDF]
Learning-based rigid tube model predictive control
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:492-503
;[abs][Download PDF]
A data-driven Riccati equation
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:504-513
;[abs][Download PDF]
Nonconvex scenario optimization for data-driven reachability
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:514-527
;[abs][Download PDF]
Uncertainty quantification and robustification of model-based controllers using conformal prediction
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:528-540
;[abs][Download PDF]
Learning for CasADi: Data-driven Models in Numerical Optimization
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:541-553
;[abs][Download PDF]
Neural operators for boundary stabilization of stop-and-go traffic
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:554-565
;[abs][Download PDF]
Submodular information selection for hypothesis testing with misclassification penalties
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:566-577
;[abs][Download PDF]
Learning and deploying robust locomotion policies with minimal dynamics randomization
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:578-590
;[abs][Download PDF]
Learning flow functions of spiking systems
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:591-602
;[abs][Download PDF]
Safe learning in nonlinear model predictive control
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:603-614
;[abs][Download PDF]
Efficient skill acquisition for insertion tasks in obstructed environments
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:615-627
;[abs][Download PDF]
Balanced reward-inspired reinforcement learning for autonomous vehicle racing
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:628-640
;[abs][Download PDF]
An invariant information geometric method for high-dimensional online optimization
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:641-653
;[abs][Download PDF]
On the nonsmooth geometry and neural approximation of the optimal value function of infinite-horizon pendulum swing-up
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:654-666
;[abs][Download PDF]
Data-driven robust covariance control for uncertain linear systems
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:667-678
;[abs][Download PDF]
Combining model-based controller and ML advice via convex reparameterization
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:679-693
;[abs][Download PDF]
Pointwise-in-time diagnostics for reinforcement learning during training and runtime
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:694-706
;[abs][Download PDF]
Expert with clustering: Hierarchical online preference learning framework
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:707-718
;[abs][Download PDF]
Verification of neural reachable tubes via scenario optimization and conformal prediction
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:719-731
;[abs][Download PDF]
Random features approximation for control-affine systems
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:732-744
;[abs][Download PDF]
Hacking predictors means hacking cars: Using sensitivity analysis to identify trajectory prediction vulnerabilities for autonomous driving security
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:745-757
;[abs][Download PDF]
Rademacher complexity of neural ODEs via Chen-Fliess series
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:758-769
;[abs][Download PDF]
Robust cooperative multi-agent reinforcement learning: A mean-field type game perspective
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:770-783
;[abs][Download PDF]
Learning $\epsilon$-Nash equilibrium stationary policies in stochastic games with unknown independent chains using online mirror descent
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:784-795
;[abs][Download PDF]
Uncertainty informed optimal resource allocation with Gaussian process based Bayesian inference
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:796-812
;[abs][Download PDF]
Improving sample efficiency of high dimensional Bayesian optimization with MCMC
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:813-824
;[abs][Download PDF]
SpOiLer: Offline reinforcement learning using scaled penalties
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:825-838
;[abs][Download PDF]
Towards safe multi-task Bayesian optimization
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:839-851
;[abs][Download PDF]
Mixing classifiers to alleviate the accuracy-robustness trade-off
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:852-865
;[abs][Download PDF]
Design of observer-based finite-time control for inductively coupled power transfer system with random gain fluctuations
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:866-875
;[abs][Download PDF]
Learning robust policies for uncertain parametric Markov decision processes
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:876-889
;[abs][Download PDF]
Conditions for parameter unidentifiability of linear ARX systems for enhancing security
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:890-901
;[abs][Download PDF]
Meta-learning linear quadratic regulators: a policy gradient MAML approach for model-free LQR
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:902-915
;[abs][Download PDF]
A large deviations perspective on policy gradient algorithms
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:916-928
;[abs][Download PDF]
Deep model-free KKL observer: A switching approach
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:929-940
;[abs][Download PDF]
In vivo learning-based control of microbial populations density in bioreactors
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:941-953
;[abs][Download PDF]
Bounded robustness in reinforcement learning via lexicographic objectives
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:954-967
;[abs][Download PDF]
System-level safety guard: Safe tracking control through uncertain neural network dynamics models
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:968-979
;[abs][Download PDF]
Nonasymptotic regret analysis of adaptive linear quadratic control with model misspecification
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:980-992
;[abs][Download PDF]
Error bounds, PL condition, and quadratic growth for weakly convex functions, and linear convergences of proximal point methods
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:993-1005
;[abs][Download PDF]
Parameterized fast and safe tracking (FaSTrack) using DeepReach
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1006-1017
;[abs][Download PDF]
Probabilistic ODE solvers for integration error-aware numerical optimal control
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1018-1032
;[abs][Download PDF]
Event-triggered safe Bayesian optimization on quadcopters
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1033-1045
;[abs][Download PDF]
Finite-time complexity of incremental policy gradient methods for solving multi-task reinforcement learning
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1046-1057
;[abs][Download PDF]
Convergence guarantees for adaptive model predictive control with kinky inference
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1058-1070
;[abs][Download PDF]
Convex approximations for a bi-level formulation of data-enabled predictive control
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1071-1082
;[abs][Download PDF]
PDE control gym: A benchmark for data-driven boundary control of partial differential equations
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1083-1095
;[abs][Download PDF]
Towards bio-inspired control of aerial vehicle: Distributed aerodynamic parameters for state prediction
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1096-1106
;[abs][Download PDF]
Residual learning and context encoding for adaptive offline-to-online reinforcement learning
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1107-1121
;[abs][Download PDF]
CoVO-MPC: Theoretical analysis of sampling-based MPC and optimal covariance design
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1122-1135
;[abs][Download PDF]
Stable modular control via contraction theory for reinforcement learning
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1136-1148
;[abs][Download PDF]
Data-driven bifurcation analysis via learning of homeomorphism
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1149-1160
;[abs][Download PDF]
A learning-based framework to adapt legged robots on-the-fly to unexpected disturbances
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1161-1173
;[abs][Download PDF]
On task-relevant loss functions in meta-reinforcement learning
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1174-1186
;[abs][Download PDF]
State-wise safe reinforcement learning with pixel observations
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1187-1201
;[abs][Download PDF]
Multi-agent assignment via state augmented reinforcement learning
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1202-1213
;[abs][Download PDF]
PlanNetX: Learning an efficient neural network planner from MPC for longitudinal control
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1214-1227
;[abs][Download PDF]
Mapping back and forth between model predictive control and neural networks
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1228-1240
;[abs][Download PDF]
A multi-modal distributed learning algorithm in reproducing kernel Hilbert spaces
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1241-1252
;[abs][Download PDF]
Towards model-free LQR control over rate-limited channels
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1253-1265
;[abs][Download PDF]
Learning true objectives: Linear algebraic characterizations of identifiability in inverse reinforcement learning
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1266-1277
;[abs][Download PDF]
Safety filters for black-box dynamical systems by learning discriminating hyperplanes
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1278-1291
;[abs][Download PDF]
Lagrangian inspired polynomial estimator for black-box learning and control of underactuated systems
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1292-1304
;[abs][Download PDF]
From raw data to safety: Reducing conservatism by set expansion
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1305-1317
;[abs][Download PDF]
Dynamics harmonic analysis of robotic systems: Application in data-driven Koopman modelling
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1318-1329
;[abs][Download PDF]
Recursively feasible shrinking-horizon MPC in dynamic environments with conformal prediction guarantees
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1330-1342
;[abs][Download PDF]
Multi-modal conformal prediction regions by optimizing convex shape templates
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1343-1356
;[abs][Download PDF]
Learning locally interacting discrete dynamical systems: Towards data-efficient and scalable prediction
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1357-1369
;[abs][Download PDF]
How safe am I given what I see? Calibrated prediction of safety chances for image-controlled autonomy
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1370-1387
;[abs][Download PDF]
Convex neural network synthesis for robustness in the 1-norm
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1388-1399
;[abs][Download PDF]
Increasing information for model predictive control with semi-Markov decision processes
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1400-1414
;[abs][Download PDF]
Physically consistent modeling & identification of nonlinear friction with dissipative Gaussian processes
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1415-1426
;[abs][Download PDF]
STEMFold: Stochastic temporal manifold for multi-agent interactions in the presence of hidden agents
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1427-1439
;[abs][Download PDF]
Distributed on-the-fly control of multi-agent systems with unknown dynamics: Using limited data to obtain near-optimal control
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1440-1451
;[abs][Download PDF]
CACTO-SL: Using Sobolev learning to improve continuous actor-critic with trajectory optimization
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1452-1463
;[abs][Download PDF]
Multi-agent coverage control with transient behavior consideration
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1464-1476
;[abs][Download PDF]
Data driven verification of positive invariant sets for discrete, nonlinear systems
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1477-1488
;[abs][Download PDF]
Adaptive teaching in heterogeneous agents: Balancing surprise in sparse reward scenarios
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1489-1501
;[abs][Download PDF]
Can a transformer represent a Kalman filter?
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1502-1512
;[abs][Download PDF]
Data-driven simulator for mechanical circulatory support with domain adversarial neural process
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1513-1525
;[abs][Download PDF]
DC4L: Distribution shift recovery via data-driven control for deep learning models
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1526-1538
;[abs][Download PDF]
QCQP-Net: Reliably learning feasible alternating current optimal power flow solutions under constraints
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1539-1551
;[abs][Download PDF]
A deep learning approach for distributed aggregative optimization with users’ Feedback
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1552-1564
;[abs][Download PDF]
A framework for evaluating human driver models using neuroimaging
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1565-1578
;[abs][Download PDF]
Deep Hankel matrices with random elements
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1579-1591
;[abs][Download PDF]
Robust exploration with adversary via Langevin Monte Carlo
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1592-1605
;[abs][Download PDF]
Generalized constraint for probabilistic safe reinforcement learning
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1606-1618
;[abs][Download PDF]
Neural processes with event triggers for fast adaptation to changes
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1619-1632
;[abs][Download PDF]
Data-driven strategy synthesis for stochastic systems with unknown nonlinear disturbances
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1633-1645
;[abs][Download PDF]
Growing Q-networks: Solving continuous control tasks with adaptive control resolution
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1646-1661
;[abs][Download PDF]
Hamiltonian GAN
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1662-1674
;[abs][Download PDF]
Do no harm: A counterfactual approach to safe reinforcement learning
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1675-1687
;[abs][Download PDF]
Wasserstein distributionally robust regret-optimal control over infinite-horizon
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1688-1701
;[abs][Download PDF]
Probably approximately correct stability of allocations in uncertain coalitional games with private sampling
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1702-1714
;[abs][Download PDF]
Reinforcement learning-driven parametric curve fitting for snake robot gait design
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1715-1727
;[abs][Download PDF]
Pontryagin neural operator for solving general-sum differential games with parametric state constraints
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1728-1740
;[abs][Download PDF]
Adaptive neural network based control approach for building energy control under changing environmental conditions
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1741-1752
;[abs][Download PDF]
Physics-constrained learning of PDE systems with uncertainty quantified port-Hamiltonian models
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1753-1764
;[abs][Download PDF]
Proto-MPC: An encoder-prototype-decoder approach for quadrotor control in challenging winds
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1765-1776
;[abs][Download PDF]
Efficient imitation learning with conservative world models
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1777-1790
;[abs][Download PDF]
Restless bandits with rewards generated by a linear Gaussian dynamical system
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1791-1802
;[abs][Download PDF]
subscribe via RSS