AGI’s Hierarchical Component Approach to Unsolvable by Direct Statistical Methods Complex Problems
Vladimir Sergeevich Smolin, Sergey Mikhailovich Sokolov · 2023
The amazing deep neural network (DNN) advances over the past 10 years have made it possible, if there is enough data and computing power, to achieve solutions to unexpectedly complex problems. But DNN does not explicitly use decomposition, the main advancement method in complicated task solving. The automatic complex scenes decomposition can be carried out based on mapping by a neural network. The problem is the impossibility to map complex objects and phenomena state spaces. The hierarchical complex scene’s division into simple components can be a key for solving the problem. The hierarchically organized structure of simple objects and phenomena maps of different abstraction levels can make it possible to solve problems in a complex environment, in which all properties cannot directly be revealed by statistical methods. Operation modes of such a hierarchical structure can be correlated with terms used in philosophy and psychology.