Universidad Nacional, Autánoma de México.
Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas.
Artif Life. 2023 May 1;29(2):153-167. doi: 10.1162/artl_a_00397.
Even when concepts similar to emergence have been used since antiquity, we lack an agreed definition. However, emergence has been identified as one of the main features of complex systems. Most would agree on the statement "life is complex." Thus understanding emergence and complexity should benefit the study of living systems. It can be said that life emerges from the interactions of complex molecules. But how useful is this to understanding living systems? Artificial Life (ALife) has been developed in recent decades to study life using a synthetic approach: Build it to understand it. ALife systems are not so complex, be they soft (simulations), hard (robots), or wet(protocells). Thus, we can aim at first understanding emergence in ALife, to then use this knowledge in biology. I argue that to understand emergence and life, it becomes useful to use information as a framework. In a general sense, I define emergence as information that is not present at one scale but present at another. This perspective avoids problems of studying emergence from a materialist framework and can also be useful in the study of self-organization and complexity.
即使自古就有与涌现类似的概念被使用，我们仍然缺乏一个被认可的定义。然而，涌现已被确定为复杂系统的主要特征之一。大多数人都会认同“生命是复杂的”这一说法。因此，理解涌现和复杂性应该有益于对生命系统的研究。可以说，生命是从复杂分子的相互作用中涌现出来的。但是，这对于理解生命系统有什么帮助呢？人工生命（ALife）在最近几十年中得到了发展，它采用合成方法来研究生命：通过构建来理解。ALife 系统并不那么复杂，无论是软（模拟）、硬（机器人）还是湿（原细胞）。因此，我们可以首先在 ALife 中致力于理解涌现，然后将这些知识应用于生物学。我认为，要理解涌现和生命，使用信息作为框架是很有用的。从广义上讲，我将涌现定义为在一个尺度上不存在但在另一个尺度上存在的信息。这种观点避免了从唯物主义框架研究涌现所带来的问题，也可以在自组织和复杂性的研究中发挥作用。
