No-regret learning for repeated non-cooperative games with lossy bandits

Liu, Wenting; Lei, Jinlong; Yi, Peng; Hong, Yiguang

doi:10.1016/j.automatica.2023.111455

Automatica

2024

DOI: 10.1016/j.automatica.2023.111455

|View full text |Cite

No-regret learning for repeated non-cooperative games with lossy bandits

Wenting Liu,

Jinlong Lei,

Peng Yi

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article2

Relationship

Self Cite0

Independent2

Authors

Journals

Cited by 2 publications

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Robust distributed Nash equilibrium solution for multi‐agent differential graphical games

Zhang,

Cui

et al. 2024

IET Control Theory & Appl

View full text Add to dashboard Cite

This paper studies the differential graphical games for linear multi‐agent systems with modelling uncertainties. A robust optimal control policy that seeks the distributed Nash equilibrium solution and guarantees the leader‐following consensus is designed. The weighting matrices rely on modelling uncertainties, leading to the Nash equilibrium solution, and the solution can be obtained by solving a decoupled algebraic Riccati equation. Simulation studies are finally reported to illustrate the effectiveness of proposed policy.

show abstract

Robust distributed Nash equilibrium solution for multi‐agent differential graphical games

Zhang,

Cui

et al. 2024

IET Control Theory & Appl

View full text Add to dashboard Cite

show abstract

Adaptive Decision-Making in Attack-Defense Games With Bayesian Inference of Rationality Level

Fang,

2024

IEEE Trans. Ind. Electron.

View full text Add to dashboard Cite

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

No-regret learning for repeated non-cooperative games with lossy bandits

Cited by 2 publications

References 38 publications

Robust distributed Nash equilibrium solution for multi‐agent differential graphical games

Robust distributed Nash equilibrium solution for multi‐agent differential graphical games

Adaptive Decision-Making in Attack-Defense Games With Bayesian Inference of Rationality Level

Contact Info

Product

Resources

About