Editorial: Brain-inspired cognition and understanding for next-generation AI: Computational models, architectures and learning algorithms

Yuqi Han; Chenwei Deng; Guang-Bin Huang

doi:10.3389/fnins.2023.1169027

Editorial: Brain-inspired cognition and understanding for next-generation AI: Computational models, architectures and learning algorithms

Front Neurosci. 2023 Mar 24:17:1169027. doi: 10.3389/fnins.2023.1169027. eCollection 2023.

Authors

Yuqi Han^{1

2}, Chenwei Deng¹, Guang-Bin Huang³

Affiliations

¹ School of Information and Electronics, Beijing Institute of Technology, Beijing, China.
² Department of Computer Science and Technology, Tsinghua University, Beijing, China.
³ School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore.

No abstract available

Keywords: artificial intelligence; brain-inspired cognition; machine learning; multimodal perception; perception science.

Publication types

Editorial

Grants and funding

This work was supported by National Natural Science Foundation of China (NSFC) under Grant 62171040 and the China Postdoctoral Science Foundation under Grant 2021TQ0177.