<?xml version="1.0" encoding="utf-8"?>
<rss version="2.0">
    <channel>
        <title>AGI Experime</title>
        <link>https://paragraph.com/@future</link>
        <description>本文探讨了人工智能通用智能（AGI）的概念和实现方法。AGI是指机器具备接近或超越人类智能的能力，其核心要素包括超大规模神经网络系统、感觉系统和动作系统，以及维持智能体在环境中可持续互动的自身生命维持系统和主动优化自身生存能力的动机系统。人类智能的形成过程是通过结构与环境的互动演化过程产生的，这种物理结构被抽象为特定的智能程序和知识数据。实现AGI通用人工智能的方法可以参考人类智能的物理结构，制造具备神经网络系统、感觉系统、行动系统的智能体系统，并建立保证智能体可持续与环境互动的智能体支持系统。同时，还需要人工设定或自然生成智能体以提升自身生存能力为首要目标的动机系统。最后，本文提出了一个“AGI通用人工智能思想实验”作为例子，以展示如何实现AGI通用人工智能的方法。 关键词：通用人工智能；人类智能；演化；思想实验 Abstract: This paper discusses the concept and implementation method of artificial intelligence general intelligence (AGI). AGI means that the machine has the ability to approach or surpass human intelligence, and its core elements include super-large-scale neural network system, sensory system and action system, as well as its own life support system to maintain the sustainable interaction of agents in the environment and the motivation system to actively optimize its own viability. The formation process of human intelligence is produced through the interactive evolution process of structure and environment, and this physical structure is abstracted into specific intelligent programs and knowledge data. The method of realizing AGI general artificial intelligence can refer to the physical structure of human intelligence, make an agent system with neural network system, sensory system and action system, and establish an agent support system to ensure the agent's sustainable interaction with the environment. At the same time, it is necessary to manually set or naturally generate an agent's motivation system with the primary goal of improving its own viability. Finally, this paper puts forward an "AGI general artificial intelligence thought experiment" as an example to show how to realize AGI general artificial intelligence.  Keywords: general artificial intelligence; Human intelligence; Evolution; Thought experiment</description>
        <lastBuildDate>Wed, 08 Apr 2026 23:35:54 GMT</lastBuildDate>
        <docs>https://validator.w3.org/feed/docs/rss2.html</docs>
        <generator>https://github.com/jpmonette/feed</generator>
        <language>en</language>
        <image>
            <title>AGI Experime</title>
            <url>https://storage.googleapis.com/papyrus_images/7a5b07c755bb3f6ef8b442336fbc0a06.jpg</url>
            <link>https://paragraph.com/@future</link>
        </image>
        <copyright>All rights reserved</copyright>
    </channel>
</rss>