van Gerven Marcel
Computational Cognitive Neuroscience Lab, Department of Artificial Intelligence, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands.
Front Comput Neurosci. 2017 Dec 7;11:112. doi: 10.3389/fncom.2017.00112. eCollection 2017.
New developments in AI and neuroscience are revitalizing the quest to understanding natural intelligence, offering insight about how to equip machines with human-like capabilities. This paper reviews some of the computational principles relevant for understanding natural intelligence and, ultimately, achieving strong AI. After reviewing basic principles, a variety of computational modeling approaches is discussed. Subsequently, I concentrate on the use of artificial neural networks as a framework for modeling cognitive processes. This paper ends by outlining some of the challenges that remain to fulfill the promise of machines that show human-like intelligence.
人工智能和神经科学的新进展正在重振对理解自然智能的探索,为如何赋予机器类人能力提供了见解。本文回顾了一些与理解自然智能以及最终实现通用人工智能相关的计算原理。在回顾基本原理之后,讨论了各种计算建模方法。随后,我专注于将人工神经网络作为一种对认知过程进行建模的框架。本文最后概述了在实现具有类人智能的机器的前景方面仍然存在的一些挑战。