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11/05/2021
Improved Regret Analysis for Variance-Adaptive Linear Bandits and Horizon-Free Linear Mixture MDPs
In online learning problems, exploiting low variance plays an important ...
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10/27/2021
Training Wasserstein GANs without gradient penalties
We propose a stable method to train Wasserstein generative adversarial n...
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09/15/2021
Infusing model predictive control into meta-reinforcement learning for mobile robots in dynamic environments
The successful operation of mobile robots requires them to rapidly adapt...
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05/03/2021
Distributionally robust risk map for learning-based motion planning and control: A semidefinite programming approach
This paper proposes a novel safety specification tool, called the distri...
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10/27/2020
Hamilton-Jacobi Deep Q-Learning for Deterministic Continuous-Time Systems with Lipschitz Continuous Controls
In this paper, we propose Q-learning algorithms for continuous-time dete...
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03/05/2020
Learning-based distributionally robust motion control with Gaussian processes
Safety is a critical issue in learning-based robotic and autonomous syst...
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02/24/2020
Safe reinforcement learning for probabilistic reachability and safety specifications: A Lyapunov-based approach
Emerging applications in robotics and autonomous systems, such as autono...
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01/14/2020
Wasserstein Distributionally Robust Motion Control for Collision Avoidance Using Conditional Value-at-Risk
In this paper, a risk-aware motion control scheme is considered for mobi...
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12/23/2019