In establishment of a general-purpose artificial intelligence system, the machine simulates similarity, repeatability and adjacency of information, and stores the demand, award/penalty and emotion symbols together with related low-level features as a preset relation network. When the machine encounters input information, the machine iteratively identifies low-level features in the input information and stores them in a memory according to a simultaneous storage method. With the low-level features as nodes and the similarity, repeatability and adjacency relations between nodes as connection relations, the machine establish relations between the low-level features and the demand, award/penalty and emotion symbols to extend the relation network. The machine uses the low-level features and searches for related low-level features through a chain associative activation process, searches for imitable experiences through segmented simulation, reassembles the experiences according to a principle of benefit-seeking and harm-avoiding to form an optimal response path.