It is well known that the length of a syntactic dependency determines its online memory cost. Thus, the problem of the placement of a head and its dependents (complements or modifiers) that minimizes online memory is equivalent to the problem of the minimum linear arrangement of a star tree. However, how that length is translated into a cognitive cost is not known. Here it is shown that the online memory cost is minimized when the head is placed at the center, regardless of the function that transforms length into cost, provided only that this function is strictly monotonically increasing. Online memory defines a quasi-convex adaptive landscape with a single central minimum if the number of elements is odd and two central minima if that number is even. We discuss various aspects of the dynamics of word order of subject (S), verb (V) and object (O) from a complex systems perspective. We suggest that word orders tend to evolve by swapping adjacent constituents from and initial or early SOV configuration that is attracted towards a central word order by online memory minimization. We also suggest that the stability of SVO is to due at least two factors, the quasi-convex shape of the adaptive landscape in the online memory dimension and online memory adaptations to avoid regression to SOV. Although OVS is also optimal for placing the verb at the center, its low frequency is explained by its long distance to the seminal SOV in the permutation space.

通过将元素数量视为从奇数到偶数的前一个情况的过度，论文研究了在线存储成本的诸多方面，并证明将核心放在中心可以最小化在线内存成本。

最小化在线存储的头部位置:一种复杂系统方法