Ehresmann A C, Vanbremeersch J P
Facultè de Mathématiques et d'Informatique, Amiens, France.
Biosystems. 1997;43(1):25-40. doi: 10.1016/s0303-2647(97)01690-0.
The aim of this paper is to evaluate the role of symmetry and symmetry-breaking processes on the complex information processing developed by hierarchical evolutionary natural systems, such as biological, neural, social or cultural systems. The study is conducted in the frame of the Memory Evolutive Systems, which give a mathematical model of these systems. The dynamics of a MES is modulated by the competition between a net of internal regulation centers which act apart-but encode overlapping strategies which have to be equilibrated. The main characteristics of these systems, at the root of their complexity and adaptability, is a symmetry-breaking in the passage from a higher (or macro) level to a lower (or micro) level: several disparate sub-systems with different comportments at the micro level can be undistinguishable at the higher macro level because of a similar macro behavior (Multiplicity Principle). It is responsible for the development of a dialectics between heterogeneous regulation centers, and for the emergence in time of more and more complex objects. An application to neural systems vindicates an emergentist dynamical reduction of mental states to physical states.
本文旨在评估对称性和对称破缺过程在由层次进化自然系统（如生物、神经、社会或文化系统）所发展出的复杂信息处理中的作用。该研究是在记忆进化系统的框架内进行的，记忆进化系统给出了这些系统的数学模型。一个记忆进化系统的动力学是由内部调节中心网络之间的竞争所调节的，这些调节中心各自独立运作，但编码着必须达到平衡的重叠策略。这些系统复杂性和适应性的根源，其主要特征在于从较高（或宏观）层次到较低（或微观）层次的转变过程中出现的对称破缺：由于宏观行为相似（多重性原理），几个在微观层次具有不同行为的不同子系统在较高的宏观层次可能是无法区分的。这导致了异质调节中心之间辩证法的发展，以及越来越复杂的对象随时间的出现。对神经系统的应用证明了心理状态向物理状态的涌现主义动态还原。
