Prudkov Pavel
Cogsydata.ltd, Jerusalem, Israel.
Front Artif Intell. 2025 Jun 18;8:1588726. doi: 10.3389/frai.2025.1588726. eCollection 2025.
Humans are goal-directed agents and intelligence is suggested to be a characteristic of such agents. AGI can be achieved following the principle of the goals-means correspondence that posits the necessary condition for achieving a goal is the correspondence between the goal and the means. The goals-means correspondence is used in all architectures underlying intelligent systems. There are two conventional architectures regarding how the correspondence can be established. One conventional architecture that is based on observations of animals, is intelligent agents whose goals, means, or criteria for its construction are determined jointly at the moment of the birth of an agent. The other conventional architecture that is based on the analysis of human actions, defines intelligent agents whose goals and means are constructed arbitrarily and independently from each other. The conventional architectures cannot explain human actions and thinking. Since the conventional architectures underlie all artificial intelligent systems these systems are insufficient to construct AGI. The formal analysis of architectures demonstrates that there is another architecture in that arbitrary goals and means are constructed jointly on the basis of the criterion of minimal construction costs. This architecture is suggested to underlie human goal-directed processes. The view on humans as goal-directed agents constructing goals and means jointly allows creating an AGI agent that is capable of functioning in real situations. Unlike conventional AI agents that have an unaltered structure, the structure of agents in the new architecture is alterable. The development of an AGI agent may be similar to human growth from an infant to an adult. A model including a simple agent based on the new architecture, is considered. In the model the agent wanders in a quadrangular field filled with various objects that stimulate the agent to move in several directions simultaneously, thus trapping the agent. However, changing its structure the agent constructs goal-directed processes; therefore it is capable of leaving traps.
人类是目标导向型主体，而智能被认为是此类主体的一种特征。通用人工智能（AGI）可以遵循目标 - 手段对应原则来实现，该原则假定实现目标的必要条件是目标与手段之间的对应。目标 - 手段对应应用于智能系统的所有底层架构。关于如何建立这种对应关系，有两种传统架构。一种基于对动物的观察的传统架构是智能主体，其目标、手段或构建它的标准在主体诞生之时共同确定。另一种基于对人类行为分析的传统架构定义的智能主体，其目标和手段是相互独立且任意构建的。这些传统架构无法解释人类行为和思维。由于这些传统架构是所有人工智能系统的基础，所以这些系统不足以构建通用人工智能。对架构的形式分析表明，存在另一种架构，即基于最小构建成本标准共同构建任意目标和手段。这种架构被认为是人类目标导向过程的基础。将人类视为共同构建目标和手段的目标导向型主体的观点，使得创建一个能够在实际情况中运行的通用人工智能主体成为可能。与结构不变的传统人工智能主体不同，新架构中主体的结构是可改变的。通用人工智能主体的发展可能类似于人类从婴儿到成人的成长过程。考虑了一个包含基于新架构的简单主体的模型。在该模型中，主体在一个充满各种物体的四边形区域中徘徊，这些物体刺激主体同时向多个方向移动，从而困住主体。然而，通过改变其结构，主体构建了目标导向过程；因此它能够摆脱陷阱。
