论文标题
共同进化混合智能的认知架构
Cognitive Architecture for Co-Evolutionary Hybrid Intelligence
论文作者
论文摘要
本文质疑强大（一般）以数据为中心的人工智能（AI）的可行性。讨论了这种智能的缺点。作为替代方案，提出了共同进化的混合智能的概念。它基于人类和机器的认知互操作性。对现有的认知体系结构的构建方法进行了分析。考虑了一个架构将人类无缝纳入智能问题解决的循环中。该文章的组织如下。第一部分包含对以数据为中心的智能系统的批评。指出基于这种智能的强大人工智能不可能创建强大的人工智能的原因。第二部分简要介绍了共同进化的混合智能的概念，并显示了其优势。第三部分概述和分析了现有的认知体系结构。得出的结论是，许多人不认为人类是智能数据处理过程的一部分。下一部分讨论了共同进化混合智能的认知架构，并提供了与人类的融合。它得出了关于与人类在解决问题的循环中开发智能系统的可行性的一般结论。
This paper questions the feasibility of a strong (general) data-centric artificial intelligence (AI). The disadvantages of this type of intelligence are discussed. As an alternative, the concept of co-evolutionary hybrid intelligence is proposed. It is based on the cognitive interoperability of man and machine. An analysis of existing approaches to the construction of cognitive architectures is given. An architecture seamlessly incorporates a human into the loop of intelligent problem solving is considered. The article is organized as follows. The first part contains a critique of data-centric intelligent systems. The reasons why it is impossible to create a strong artificial intelligence based on this type of intelligence are indicated. The second part briefly presents the concept of co-evolutionary hybrid intelligence and shows its advantages. The third part gives an overview and analysis of existing cognitive architectures. It is concluded that many do not consider humans part of the intelligent data processing process. The next part discusses the cognitive architecture for co-evolutionary hybrid intelligence, providing integration with humans. It finishes with general conclusions about the feasibility of developing intelligent systems with humans in the problem-solving loop.
