On the construction of artificial general intelligence based on the correspondence between goals and means

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.