Why Deep Neural Nets Cannot Ever Match Biological Intelligence and What To Do About It?

doi:10.1007/s11633-017-1093-8

CORC > 自动化研究所 > 中国科学院自动化研究所 > 学术期刊 > International Journal of Automation and Computing

	Why Deep Neural Nets Cannot Ever Match Biological Intelligence and What To Do About It?
	Danko Nikolic 1,2,3
刊名	International Journal of Automation and Computing
	2017
卷号	14 期号:5 页码:532-541
关键词	Artificial intelligence neural networks strong artificial intelligence practopoiesis, machine learning.
ISSN号	1476-8186
DOI	10.1007/s11633-017-1093-8
文献子类	IJAC-HIC-2016-12-315.pdf
英文摘要	The recently introduced theory of practopoiesis offers an account on how adaptive intelligent systems are organized. According to that theory, biological agents adapt at three levels of organization and this structure applies also to our brains. This is referred to as tri-traversal theory of the organization of mind or for short, a T3-structure. To implement a similar T3-organization in an artificially intelligent agent, it is necessary to have multiple policies, as usually used as a concept in the theory of reinforcement learning. These policies have to form a hierarchy. We define adaptive practopoietic systems in terms of hierarchy of policies and calculate whether the total variety of behavior required by real-life conditions of an adult human can be satisfactorily accounted for by a traditional approach to artificial intelligence based on T2-agents, or whether a T3-agent is needed instead. We conclude that the complexity of real life can be dealt with appropriately only by a T3-agent. This means that the current approaches to artificial intelligence, such as deep architectures of neural networks, will not suffice with fixed network architectures. Rather, they will need to be equipped with intelligent mechanisms that rapidly alter the architectures of those networks.
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/42477]
专题	自动化研究所_学术期刊_International Journal of Automation and Computing
作者单位	1.Department of Psychology, Faculty of Humanities and Social Sciences, University of Zagreb, Croatia 2.Frankfurt Institute for Advanced Studies (FIAS), Ruth-Moufang-Straße 1, D-60438 Frankfurt/M, Germany 3.DXC Technology, Frankfurt am Main, Germany
推荐引用方式 GB/T 7714	Danko Nikolic. Why Deep Neural Nets Cannot Ever Match Biological Intelligence and What To Do About It?[J]. International Journal of Automation and Computing,2017,14(5):532-541.
APA	Danko Nikolic.(2017).Why Deep Neural Nets Cannot Ever Match Biological Intelligence and What To Do About It?.International Journal of Automation and Computing,14(5),532-541.
MLA	Danko Nikolic."Why Deep Neural Nets Cannot Ever Match Biological Intelligence and What To Do About It?".International Journal of Automation and Computing 14.5(2017):532-541.