MARS: Multiagent Reinforcement Learning for Spatial—Spectral and Temporal Feature Selection in EEG-Based BCI-Reference-Cited by-同舟云学术

MARS: Multiagent Reinforcement Learning for Spatial—Spectral and Temporal Feature Selection in EEG-Based BCI

Published:2024-05 Issue:5 Volume:54 Page:3084-3096
ISSN:2168-2216
Container-title:IEEE Transactions on Systems, Man, and Cybernetics: Systems
language:
Short-container-title:IEEE Trans. Syst. Man Cybern, Syst.

Author:

Shin Dong-Hee¹^ORCID,Son Young-Han¹^ORCID,Kim Jun-Mo¹^ORCID,Ahn Hee-Jun¹,Seo Jun-Ho¹,Ji Chang-Hoon¹^ORCID,Han Ji-Wung¹,Lee Byung-Jun¹^ORCID,Won Dong-Ok²^ORCID,Kam Tae-Eui¹^ORCID

Affiliation:

1. Department of Artificial Intelligence, Korea University, Seoul, Republic of Korea

2. Department of Artificial Intelligence Convergence, Hallym University, Chuncheon, Republic of Korea

Funder

Institute of Information and Communications Technology Planning and Evaluation

Korea Government [MSIT, Artificial Intelligence Graduate School Program (Korea University)]

National Research Foundation of Korea

Korea Government

Development of AI Autonomy and Knowledge Enhancement for AI Agent Collaboration

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6221021/10500882/10426745.pdf?arnumber=10426745

Reference58 articles.

1. Direct-Sense Brain–Computer Interfaces and Wearable Computers

2. A Systematic Deep Learning Model Selection for P300-Based Brain-Computer Interfaces

3. Classification of EEG Signals on VEP-Based BCI Systems With Broad Learning

4. EEG-Based Drowsiness Detection With Fuzzy Independent Phase-Locking Value Representations Using Lagrangian-Based Deep Neural Networks

5. Emotion Classification Using EEG Brain Signals and the Broad Learning System

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