Papers
546 papers found
Learning without Knowing: Unobserved Context in Continuous Transfer Reinforcement Learning
Chenyu Liu, Yan Zhang, Yi Shen et al.
LEOC: A Principled Method in Integrating Reinforcement Learning and Classical Control Theory
Naifu Zhang, Nicholas Capel
Linear Regression over Networks with Communication Guarantees
Konstantinos Gatsis
Maximum Likelihood Signal Matrix Model for Data-Driven Predictive Control
Mingzhou Yin, Andrea Iannelli, Roy S. Smith
Minimax Adaptive Control for a Finite Set of Linear Systems
Anders Rantzer
Near-Optimal Data Source Selection for Bayesian Learning
Lintao Ye, Aritra Mitra, Shreyas Sundaram
Nested Mixture of Experts: Cooperative and Competitive Learning of Hybrid Dynamical System
Junhyeok Ahn, Luis Sentis
Neural Lyapunov Redesign
Arash Mehrjou, Mohammad Ghavamzadeh, Bernhard Schölkopf
Non-conservative Design of Robust Tracking Controllers Based on Input-output Data
Liang Xu, Mustafa Sahin Turan, Baiwei Guo et al.
Nonlinear Data-Enabled Prediction and Control
Yingzhao Lian, Colin N. Jones
Nonlinear state-space identification using deep encoder networks
Gerben Beintema, Roland Toth, Maarten Schoukens
Offline Reinforcement Learning from Images with Latent Space Models
Rafael Rafailov, Tianhe Yu, Aravind Rajeswaran et al.
Offset-free setpoint tracking using neural network controllers
Patricia Pauli, Johannes Köhler, Julian Berberich et al.
On exploration requirements for learning safety constraints
Pierre-François Massiani, Steve Heim, Sebastian Trimpe
On the Model-Based Stochastic Value Gradient for Continuous Reinforcement Learning
Brandon Amos, Samuel Stanton, Denis Yarats et al.
On Uninformative Optimal Policies in Adaptive LQR with Unknown B-Matrix
Ingvar Ziemann, Henrik Sandberg
Optimal Algorithms for Submodular Maximization with Distributed Constraints
Alexander Robey, Arman Adibi, Brent Schlotfeldt et al.
Optimal Cost Design for Model Predictive Control
Avik Jain, Lawrence Chan, Daniel S. Brown et al.
Physics-penalised Regularisation for Learning Dynamics Models with Contact
Gabriella Pizzuto, Michael Mistry
Primal-dual Learning for the Model-free Risk-constrained Linear Quadratic Regulator
Feiran Zhao, Keyou You
Probabilistic robust linear quadratic regulators with Gaussian processes
Alexander von Rohr, Matthias Neumann-Brosig, Sebastian Trimpe
Provably Sample Efficient Reinforcement Learning in Competitive Linear Quadratic Systems
Jingwei Zhang, Zhuoran Yang, Zhengyuan Zhou et al.
Regret Bounds for Adaptive Nonlinear Control
Nicholas M. Boffi, Stephen Tu, Jean-Jacques E. Slotine
Regret-optimal measurement-feedback control
Gautam Goel, Babak Hassibi