可塑性理论：作为逆构型约束的变化能力

中文摘要 AI 辅助

可塑性在科学中被广泛用于解释系统如何变化，然而它却是从它本应解释的变化本身推断出来的。一个系统可能有许多备选状态，却一个也不实现，仍可具有可塑性。另一个系统可能被强力推向其唯一备选状态，但该变化的幅度并不能确立其可塑性。对可塑性而言，重要的不是系统移动多远，而是其当前构型在多大程度上约束了备选状态。在此，我提出可塑性作为一种前瞻性属性，是逆构型约束：一个系统具有可塑性，其程度取决于在既定表征内，其当前构型对向备选状态位移的约束强弱。对于共享功能划分、结构表征和归一化架构的系统，增加可塑性会降低将当前状态与其备选状态分隔的每一个正有限结构势垒。在固定可达性标准下，可达库可以扩展但不能收缩。在网络表征中，聚合耦合被识别为构型约束，其逆定义为可塑性。势垒降低和库嵌套是定义的结果而非组成部分。这连接了两个研究传统：量化连接性而不将其解释为可塑性，以及将可塑性视为变化能力却没有前瞻性操作度量。

英文摘要

Plasticity is invoked across the sciences to explain how systems can change, yet it is inferred from the very change it is meant to explain. A system may have many alternatives, realize none and still be plastic. Another may be driven far toward its only alternative, but the magnitude of that change does not establish its plasticity. What matters for plasticity is not how far the system moves but how strongly its present configuration constrains alternatives. Here I propose that plasticity, understood as a prospective property, is inverse configurational constraint: a system is plastic to the extent that its present configuration weakly constrains displacement toward alternatives within a declared representation. For systems sharing a functional partition, structural representation, and normalized architecture, increasing plasticity lowers every positive finite structural barrier separating the current state from its alternatives. With a fixed accessibility criterion, the accessible repertoire can expand but cannot shrink. In network representations, aggregate coupling is identified as configurational constraint, whose inverse defines plasticity. Barrier reduction and repertoire nesting are consequences, not components, of the definition. This connects two research traditions: quantifying connectivity without interpreting it as plasticity, and treating plasticity as a capacity for change without a prospective operational measure.

补充信息

备注

21 pages, 1 figure