Multi-Agent Active Learning for Distributed Black-Box Optimization
Author:
Affiliation:
1. IDSIA Dalle Molle Institute for Artificial Intelligence, SUPSI-USI, Lugano, Switzerland
2. Department of Computer Science and System Engineering, IMT School for Advanced Studies, Lucca, Italy
3. SM5 3SB, Carshalton, U.K.
Funder
HASLER STIFTUNG through Project Black-Box Optimization in Multi-Agent Networks: Towards a Distributed Learning Approach
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Control and Optimization,Control and Systems Engineering
Link
http://xplorestaging.ieee.org/ielx7/7782633/9828546/10107979.pdf?arnumber=10107979
Reference21 articles.
1. Distributed online optimization via gradient tracking with adaptive momentum;carnevale;arXiv 2009 01745,0
2. Distributed Support Vector Machines Over Dynamic Balanced Directed Networks
3. Discrete-time dynamic average consensus
4. Adam: A method for stochastic optimization;kingma;arXiv 1412 6980,2014
5. C-GLISp: Preference-Based Global Optimization Under Unknown Constraints With Applications to Controller Calibration
Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Multi-Agent Active Learning for Distributed Black-Box Optimization;IEEE Control Systems Letters;2023
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