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Neural Network Verification in Control


Sep 30, 2021
Michael Everett

* arXiv admin note: text overlap with arXiv:2108.04140 

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Demonstration-Efficient Guided Policy Search via Imitation of Robust Tube MPC


Sep 23, 2021
Andrea Tagliabue, Dong-Ki Kim, Michael Everett, Jonathan P. How

* Submitted to the 2022 IEEE Conference on Robotics and Automation (ICRA). Video: https://youtu.be/28zQFktJIqg 

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Reachability Analysis of Neural Feedback Loops


Aug 09, 2021
Michael Everett, Golnaz Habibi, Chuangchuang Sun, Jonathan P. How


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Where to go next: Learning a Subgoal Recommendation Policy for Navigation Among Pedestrians


Feb 26, 2021
Bruno Brito, Michael Everett, Jonathan P. How, Javier Alonso-Mora

* 8 pages, 6 figures 

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Efficient Reachability Analysis of Closed-Loop Systems with Neural Network Controllers


Jan 05, 2021
Michael Everett, Golnaz Habibi, Jonathan P. How


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Robustness Analysis of Neural Networks via Efficient Partitioning: Theory and Applications in Control Systems


Oct 01, 2020
Michael Everett, Golnaz Habibi, Jonathan P. How


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Certified Adversarial Robustness for Deep Reinforcement Learning


Apr 11, 2020
Michael Everett, Bjorn Lutjens, Jonathan P. How

* arXiv admin note: text overlap with arXiv:1910.12908 

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R-MADDPG for Partially Observable Environments and Limited Communication


Feb 18, 2020
Rose E. Wang, Michael Everett, Jonathan P. How

* Reinforcement Learning for Real Life (RL4RealLife) Workshop in the 36th International Conference on Machine Learning, Long Beach, California, USA, 2019 
* Reinforcement Learning for Real Life (RL4RealLife) Workshop in the 36th International Conference on Machine Learning, Long Beach, California, USA, 2019 

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Multi-agent Motion Planning for Dense and Dynamic Environments via Deep Reinforcement Learning


Jan 18, 2020
Samaneh Hosseini Semnani, Hugh Liu, Michael Everett, Anton de Ruiter, Jonathan P. How


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FASTER: Fast and Safe Trajectory Planner for Flights in Unknown Environments


Jan 09, 2020
Jesus Tordesillas, Brett T. Lopez, Michael Everett, Jonathan P. How

* Journal paper. arXiv admin note: text overlap with arXiv:1903.03558 

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Collision Avoidance in Pedestrian-Rich Environments with Deep Reinforcement Learning


Oct 24, 2019
Michael Everett, Yu Fan Chen, Jonathan P. How

* arXiv admin note: substantial text overlap with arXiv:1805.01956 

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Planning Beyond the Sensing Horizon Using a Learned Context


Aug 24, 2019
Michael Everett, Justin Miller, Jonathan P. How


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Safe Reinforcement Learning with Model Uncertainty Estimates


Mar 01, 2019
Björn Lütjens, Michael Everett, Jonathan P. How

* ICRA 2019; Presented at IROS 2018 Workshop on Machine Learning in Robot Motion Planning 

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Socially Aware Motion Planning with Deep Reinforcement Learning


May 04, 2018
Yu Fan Chen, Michael Everett, Miao Liu, Jonathan P. How

* 8 pages 

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Motion Planning Among Dynamic, Decision-Making Agents with Deep Reinforcement Learning


May 04, 2018
Michael Everett, Yu Fan Chen, Jonathan P. How


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Scalable Accelerated Decentralized Multi-Robot Policy Search in Continuous Observation Spaces


Mar 16, 2017
Shayegan Omidshafiei, Christopher Amato, Miao Liu, Michael Everett, Jonathan P. How, John Vian


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Semantic-level Decentralized Multi-Robot Decision-Making using Probabilistic Macro-Observations


Mar 16, 2017
Shayegan Omidshafiei, Shih-Yuan Liu, Michael Everett, Brett T. Lopez, Christopher Amato, Miao Liu, Jonathan P. How, John Vian


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