Papers
546 papers found
$\widetilde{O}(T^{-1})$ Convergence to (coarse) correlated equilibria in full-information general-sum Markov games
Weichao Mao, Haoran Qiu, Chen Wang et al.
Adapting image-based RL policies via predicted rewards
Weiyao Wang, Xinyuan Fang, Gregory Hager
Adaptive neural network based control approach for building energy control under changing environmental conditions
Lilli Frison, Simon Gölzhäuser
Adaptive online non-stochastic control
Naram Mhaisen, George Iosifidis
Adaptive teaching in heterogeneous agents: Balancing surprise in sparse reward scenarios
Emma Clark, Kanghyun Ryu, Negar Mehr
A data-driven Riccati equation
Anders Rantzer
A deep learning approach for distributed aggregative optimization with users’ Feedback
Riccardo Brumali, Guido Carnevale, Giuseppe Notarstefano
A framework for evaluating human driver models using neuroimaging
Christopher Strong, Kaylene Stocking, Jingqi Li et al.
A large deviations perspective on policy gradient algorithms
Wouter Jongeneel, Daniel Kuhn, Mengmeng Li
A learning-based framework to adapt legged robots on-the-fly to unexpected disturbances
Nolan Fey, He Li, Nicholas Adrian et al.
A multi-modal distributed learning algorithm in reproducing kernel Hilbert spaces
Aneesh Raghavan, Karl Henrik Johansson
An efficient data-based off-policy Q-learning algorithm for optimal output feedback control of linear systems
Mohammad Alsalti, Victor G. Lopez, Matthias A. Müller
An invariant information geometric method for high-dimensional online optimization
Zhengfei Zhang, Yunyue Wei, Yanan Sui
An investigation of time reversal symmetry in reinforcement learning
Brett Barkley, Amy Zhang, David Fridovich-Keil
Balanced reward-inspired reinforcement learning for autonomous vehicle racing
Zhen Tian, Dezong Zhao, Zhihao Lin et al.
Bounded robustness in reinforcement learning via lexicographic objectives
Daniel Jarne Ornia, Licio Romao, Lewis Hammond et al.
CACTO-SL: Using Sobolev learning to improve continuous actor-critic with trajectory optimization
Elisa Alboni, Gianluigi Grandesso, Gastone Pietro Rosati Papini et al.
Can a transformer represent a Kalman filter?
Gautam Goel, Peter Bartlett
Combining model-based controller and ML advice via convex reparameterization
Junxuan Shen, Adam Wierman, Guannan Qu
Conditions for parameter unidentifiability of linear ARX systems for enhancing security
Xiangyu Mao, Jianping He, Chengpu Yu et al.
Continual learning of multi-modal dynamics with external memory
Abdullah Akgül, Gozde Unal, Melih Kandemir
Controlgym: Large-scale control environments for benchmarking reinforcement learning algorithms
Xiangyuan Zhang, Weichao Mao, Saviz Mowlavi et al.
Convergence guarantees for adaptive model predictive control with kinky inference
Riccardo Zuliani, Raffaele Soloperto, John Lygeros
Convex approximations for a bi-level formulation of data-enabled predictive control
Xu Shang, Yang Zheng
Convex neural network synthesis for robustness in the 1-norm
Ross Drummond, Chris Guiver, Matthew Turner