论文标题
人工通用情报的方法：分析
Approaches to Artificial General Intelligence: An Analysis
论文作者
论文摘要
本文是对提出的旨在实现AGI的不同方法的分析，包括人脑仿真，AIXI和综合认知结构。首先，已经定义了本文所使用的AGI的定义，并陈述了其要求。对于提到的每种提出的方法，总结了所讨论的方法，并详细介绍了其关键过程，以展示其运作方式。然后，分析了列出的每种方法，考虑了各种因素，例如技术要求，计算能力和满足要求的适当性。得出的结论是，尽管有多种可以实现AGI的方法，例如人脑仿真和综合认知体系结构，但实现AGI的最有前途的方法是综合认知架构。这是因为发现人脑仿真需要扫描技术，这些技术很可能要等到2030年代才能提供，因此在此之前不太可能创建它。此外，集成的认知体系结构减少了计算要求和适合通用智能的合适功能，使其成为实现AGI的最可能方法。
This paper is an analysis of the different methods proposed to achieve AGI, including Human Brain Emulation, AIXI and Integrated Cognitive Architecture. First, the definition of AGI as used in this paper has been defined, and its requirements have been stated. For each proposed method mentioned, the method in question was summarized and its key processes were detailed, showcasing how it functioned. Then, each method listed was analyzed, taking various factors into consideration, such as technological requirements, computational ability, and adequacy to the requirements. It was concluded that while there are various methods to achieve AGI that could work, such as Human Brain Emulation and Integrated Cognitive Architectures, the most promising method to achieve AGI is Integrated Cognitive Architectures. This is because Human Brain Emulation was found to require scanning technologies that will most likely not be available until the 2030s, making it unlikely to be created before then. Moreover, Integrated Cognitive Architectures has reduced computational requirements and a suitable functionality for General Intelligence, making it the most likely way to achieve AGI.
