A Contradiction-Centered Model for the Emergence of Swarm Intelligence
This addresses the lack of general theories for swarm intelligence emergence, which is a problem for researchers in fields like AI and complex systems, though it appears incremental as it builds on existing models.
The paper tackles the problem of explaining the emergence of swarm intelligence by proposing a contradiction-centered model that describes conditions, dynamics, and processes, and it shows through experiments that the model has good generality for describing various swarm intelligence phenomena.
The phenomenon of emergence of swarm intelligence exists widely in nature and human society. People have been exploring the root cause of emergence of swarm intelligence and trying to establish general theories and models for emergence of swarm intelligence. However, the existing theories or models do not grasp the essence of swarm intelligence, so they lack generality and are difficult to explain various phenomena of emergence of swarm intelligence. In this paper, a contradiction-centered model for the emergence of swarm intelligence is proposed, in which the internal contradictions of individuals determine their behavior and properties, individuals are related and interact within the swarm because of competing and occupying environmental resources, interactions and swarm potential affect the internal contradictions of individuals and their distribution in the swarm, and the swarm intelligence is manifested as the specific distribution of individual contradictions. This model completely explains the conditions, dynamics, pathways, formations and processes of the emergence of swarm intelligence. In order to verify the validity of this model, several swarm intelligence systems are implemented and analyzed in this paper. The experimental results show that the model has good generality and can be used to describe the emergence of various swarm intelligence.