Symbolic Abstractions From Data: A PAC Learning Approach-Reference-Cited by-同舟云学术

Symbolic Abstractions From Data: A PAC Learning Approach

Published:2021-12-14 Issue: Volume: Page:
ISSN:
Container-title:2021 60th IEEE Conference on Decision and Control (CDC)
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Author:

Devonport Alex¹,Saoud Adnane¹,Arcak Murat¹

Affiliation:

1. University of California,Dept. of Electrical Engineering and Computer Sciences,Berkeley

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9682670/9682776/09683316.pdf?arnumber=9683316

Reference19 articles.

1. A theory of the learnable

2. Data-Driven Reachable Set Computation using Adaptive Gaussian Process Classification and Monte Carlo Methods

3. Estimating reachable sets with scenario optimization;devonport;ser Proceedings of Machine Learning Research,2020

4. Scenario-Based Probabilistic Reachable Sets for Recursively Feasible Stochastic Model Predictive Control

5. DryVR: data-driven verification and compositional reasoning for automotive systems;fan;International Conference on Computer Aided Verification,2017

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