Mimicking Associative Learning of Rats via a Neuromorphic Robot in Open Field Maze Using Spatial Cell Models

Data-driven Artificial Intelligence (AI) approaches have exhibited remarkable prowess across various cognitive tasks using extensive training data. However, the reliance on large datasets and neural networks presents challenges such as high-power consumption and limited adaptability, particularly in...

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Veröffentlicht in:	2024 International Conference on Neuromorphic Systems (ICONS) S. 299 - 306
Hauptverfasser:	Liu, Tianze, Bakr Siddique, Md Abu, An, Hongyu
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 30.07.2024
Schlagworte:	Associative Learning Biological system modeling Cells (biology) Cognition Grid Cells Navigation Neuromorphic Robotics Neuromorphics Place Cells Real-time systems Robots Rodents Testing Training data
Online-Zugang:	Volltext
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