Building autonomous systems that achieve human level intelligence is one of the primary objectives in artificial intelligence (AI). It requires the study of a wide range of functions robustly across different phases of human cognition. This paper presents a review of agent cognitive architectures in the past 20 year's AI research. Different from software structures and simulation environments, most of the architectures concerned are established from mathematics and philosophy. They are categorized according to their knowledge processing patterns-symbolic, emergent or hybrid. All the relevant literature can be accessed publicly, particularly through the Internet. Available websites are also summarized for further reference.

中文翻译：

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过去20年认知架构综述


构建实现人类智能水平的自主系统是人工智能 (AI) 的主要目标之一。它需要对人类认知不同阶段的各种功能进行稳健的研究。本文回顾了过去 20 年人工智能研究中的智能体认知架构。与软件结构和仿真环境不同，所涉及的架构大多是从数学和哲学出发建立的。它们根据知识处理模式进行分类——符号型、涌现型或混合型。所有相关文献都可以公开获取，特别是通过互联网。还总结了可用的网站以供进一步参考。