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10/12/2022
Near-Optimal Multi-Agent Learning for Safe Coverage Control
In multi-agent coverage control problems, agents navigate their environm...
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01/24/2022
Scalable Safe Exploration for Global Optimization of Dynamical Systems
Learning optimal control policies directly on physical systems is challe...
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05/27/2021
GoSafe: Globally Optimal Safe Robot Learning
When learning policies for robotic systems from data, safety is a major ...
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02/24/2021
Information Directed Reward Learning for Reinforcement Learning
For many reinforcement learning (RL) applications, specifying a reward i...
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01/19/2021
Safe and Efficient Model-free Adaptive Control via Bayesian Optimization
Adaptive control approaches yield high-performance controllers when a pr...
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10/30/2019
Safe Exploration for Interactive Machine Learning
In Interactive Machine Learning (IML), we iteratively make decisions and...
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10/29/2019
Robust Model-free Reinforcement Learning with Multi-objective Bayesian Optimization
In reinforcement learning (RL), an autonomous agent learns to perform co...
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07/02/2019
Mixed-Variable Bayesian Optimization
The optimization of expensive to evaluate, black-box, mixed-variable fun...
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05/18/2018
Reinforced Imitation: Sample Efficient Deep Reinforcement Learning for Map-less Navigation by Leveraging Prior Demonstrations
This work presents a learning-based approach for target driven map-less ...
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03/22/2018
Learning-based Model Predictive Control for Safe Exploration and Reinforcement Learning
Learning-based methods have been successful in solving complex control t...
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05/23/2017
Safe Model-based Reinforcement Learning with Stability Guarantees
Reinforcement learning is a powerful paradigm for learning optimal polic...
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06/15/2016
