论文标题

部分可观测时空混沌系统的无模型预测

Similarity Suppresses Cyclicity: Why Similar Competitors Form Hierarchies

论文作者

Cebra, Christopher, Strang, Alexander

论文摘要

竞争系统可以表现出层次(及物)和循环(不及物)结构。尽管对循环竞争的理论兴趣,它提供了更丰富的动态,并且占据了可能的竞争系统的更大子集,但大多数现实世界系统主要是传递的。为什么?在这里,我们引入了一种通用机制,即使有足够的循环空间,它也会促进传递性。考虑一个竞争系统,其中竞争者属性通过性能函数介导结果。我们证明,如果竞争成果顺利地取决于竞争对手的属性,那么类似的竞争对手会进行传统的竞争。鉴于竞争者的相似性和性能函数的平滑度,我们量化了与传递性的收敛速率。因此,我们证明了有关苹果和橙子的格言。类似的对象接受有序的比较。不同的对象可能不会。为了检验该理论,我们运行了一系列旨在模拟遗传训练算法的进化实验。我们考虑了一系列规范的bimatrix游戏和一系列随机性能功能,这些功能即使面对高度循环的游戏,也证明了我们机制的通用性。我们改变控制演化过程的训练参数,以及控制性能函数的形状参数,以评估结果的鲁棒性。这些实验表明,如果竞争对手演变以优化性能,那么他们的特征可能会融合,从而导致传递性。

Competitive systems can exhibit both hierarchical (transitive) and cyclic (intransitive) structures. Despite theoretical interest in cyclic competition, which offers richer dynamics, and occupies a larger subset of the space of possible competitive systems, most real-world systems are predominantly transitive. Why? Here, we introduce a generic mechanism which promotes transitivity, even when there is ample room for cyclicity. Consider a competitive system where outcomes are mediated by competitor attributes via a performance function. We demonstrate that, if competitive outcomes depend smoothly on competitor attributes, then similar competitors compete transitively. We quantify the rate of convergence to transitivity given the similarity of the competitors and the smoothness of the performance function. Thus, we prove the adage regarding apples and oranges. Similar objects admit well ordered comparisons. Diverse objects may not. To test that theory, we run a series of evolution experiments designed to mimic genetic training algorithms. We consider a series of canonical bimatrix games and an ensemble of random performance functions that demonstrate the generality of our mechanism, even when faced with highly cyclic games. We vary the training parameters controlling the evolution process, and the shape parameters controlling the performance function, to evaluate the robustness of our results. These experiments illustrate that, if competitors evolve to optimize performance, then their traits may converge, leading to transitivity.

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