The modeling of emergent swarm intelligence constitutes a major challenge and it has been tackled in a number of different ways. However, existing approaches fail to capture the nature of swarm intelligence and they are either too abstract for practical application or not generic enough to describe the various types of emergence phenomena. In this paper, a contradiction-centric model for swarm intelligence is proposed, in which individu-als determine their behaviors based on their internal contradictions whilst they associate and interact to update their contradictions. The model hypothesizes that 1) the emergence of swarm intelligence is rooted in the de-velopment of individuals' internal contradictions and the interactions taking place between individuals and the environment, and 2) swarm intelligence is essentially a combinative reflection of the configurations of individuals' internal contradictions and the distributions of these contradictions across individuals. The model is formally described and five swarm intelligence systems are studied to illustrate its broad applicability. The studies confirm the generic character of the model and its effectiveness for describing the emergence of various kinds of swarm intelligence; and they also demonstrate that the model is straightforward to apply, without the need for complicated computations.

翻译：涌现性群体智能的建模构成了一项重大挑战，并已通过多种不同方式得到处理。然而，现有方法未能捕捉群体智能的本质，它们要么过于抽象而难以实际应用，要么通用性不足而无法描述各类涌现现象。本文提出了一种以矛盾为核心的群体智能模型，其中个体基于其内部矛盾决定自身行为，同时通过关联与交互来更新其矛盾。该模型假设：1）群体智能的涌现根植于个体内部矛盾的发展以及个体与环境之间发生的相互作用；2）群体智能本质上是个体内部矛盾构型与这些矛盾在个体间分布情况的组合性反映。本文对模型进行了形式化描述，并通过研究五个群体智能系统以阐明其广泛适用性。研究证实了该模型的通用特性及其描述各类群体智能涌现的有效性；同时表明该模型易于应用，无需复杂计算。