2024/12/12 by Bo Yu, Yu, Bo, Jiangning Wei +11 · 1 citation
Computer Science · Neuroscience · #Reinforcement Learning in Robotics #EEG and Brain-Computer Interfaces #Computability, Logic, AI Algorithms
paper · pdf · doi:10.48550/arxiv.2412.08875
Artificial General Intelligence (AGI), widely regarded as the fundamental goal of artificial intelligence, represents the realization of cognitive capabilities that enable the handling of general tasks with human-like proficiency. Researchers in brain-inspired AI seek inspiration from the operational mechanisms of the human brain, aiming to replicate its functional rules in intelligent models. Moreover, with the rapid development of large-scale models in recent years, the concept of agents has garnered increasing attention, with researchers widely recognizing it as a necessary pathway toward achieving AGI. In this article, we propose the concept of a brain-inspired AI agent and analyze how to extract relatively feasible and agent-compatible cortical region functionalities and their associated functional connectivity networks from the complex mechanisms of the human brain. Implementing these structures within an agent enables it to achieve basic cognitive intelligence akin to human capabilities. Finally, we explore the limitations and challenges for realizing brain-inspired agents and discuss their future development.