Beyond Center for Fundamental Concepts in Science, Arizona State University, Tempe, AZ, USA.
Department of Physics, Arizona State University, Tempe, AZ, USA.
Sci Rep. 2017 Apr 20;7(1):997. doi: 10.1038/s41598-017-00810-8.
Open-ended evolution (OEE) is relevant to a variety of biological, artificial and technological systems, but has been challenging to reproduce in silico. Most theoretical efforts focus on key aspects of open-ended evolution as it appears in biology. We recast the problem as a more general one in dynamical systems theory, providing simple criteria for open-ended evolution based on two hallmark features: unbounded evolution and innovation. We define unbounded evolution as patterns that are non-repeating within the expected Poincare recurrence time of an isolated system, and innovation as trajectories not observed in isolated systems. As a case study, we implement novel variants of cellular automata (CA) where the update rules are allowed to vary with time in three alternative ways. Each is capable of generating conditions for open-ended evolution, but vary in their ability to do so. We find that state-dependent dynamics, regarded as a hallmark of life, statistically out-performs other candidate mechanisms, and is the only mechanism to produce open-ended evolution in a scalable manner, essential to the notion of ongoing evolution. This analysis suggests a new framework for unifying mechanisms for generating OEE with features distinctive to life and its artifacts, with broad applicability to biological and artificial systems.
开放式进化（OEE）与各种生物、人工和技术系统都有关联，但在计算机中进行复制一直具有挑战性。大多数理论研究都集中在开放式进化在生物学中出现的关键方面。我们将该问题重新表述为动力系统理论中的一个更普遍的问题，基于两个显著特征为开放式进化提供了简单的标准：无界进化和创新。我们将无界进化定义为在孤立系统的预期庞加莱重现时间内不重复的模式，而创新则是在孤立系统中未观察到的轨迹。作为一个案例研究，我们实现了细胞自动机（CA）的新变体，其中更新规则可以以三种不同的方式随时间变化。每一种都能够产生开放式进化的条件，但在产生这种条件的能力上有所不同。我们发现，状态依赖动力学，被认为是生命的标志，在统计学上优于其他候选机制，并且是唯一能够以可扩展的方式产生开放式进化的机制，这对持续进化的概念至关重要。该分析为统一生成开放式进化的机制提供了一个新的框架，这些机制具有生命及其人工制品的独特特征，在生物和人工系统中有广泛的适用性。
