Efficient Planning of Multi-Robot Collective Transport using Graph Reinforcement Learning with Higher Order Topological Abstraction-Reference-Cited by-同舟云学术

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Efficient Planning of Multi-Robot Collective Transport using Graph Reinforcement Learning with Higher Order Topological Abstraction

Published:2023-05-29 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Conference on Robotics and Automation (ICRA)
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Author:

Paul Steve¹,Li Wenyuan¹,Smyth Brian¹,Chen Yuzhou²,Gel Yulia³,Chowdhury Souma¹

Affiliation:

1. University at Buffalo,Department of Mechanical and Aerospace Engineering,Buffalo,NY,USA

2. Temple University,Department of Computer and Information Sciences,Philadelphia,PA,USA

3. University of Texas at Dallas,Department of Mathematical Sciences,Dallas,TX,USA

Funder

National Science Foundation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10160211/10160212/10161517.pdf?arnumber=10161517

Reference41 articles.

1. Learning combinatorial optimization algorithms over graphs;khalil;Advances in neural information processing systems,2017

2. Integration of element specific persistent homology and machine learning for protein‐ligand binding affinity prediction

3. Representation of molecular structures with persistent homology for machine learning applications in chemistry;townsend;Nature Communications,2020

4. Reconfiguring Unbalanced Distribution Networks using Reinforcement Learning over Graphs

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