An explanatory model for the emergence of evolvable units must display emerging structures that (1) preserve themselves in time (2) self-reproduce and (3) tolerate a certain amount of variation when reproducing. To tackle this challenge, here we introduce Combinatory Chemistry, an Algorithmic Artificial Chemistry based on a minimalistic computational paradigm named Combinatory Logic. The dynamics of this system comprise very few rules, it is initialised with an elementary tabula rasa state, and features conservation laws replicating natural resource constraints. Our experiments show that a single run of this dynamical system with no external intervention discovers a wide range of emergent patterns. All these structures rely on acquiring basic constituents from the environment and decomposing them in a process that is remarkably similar to biological metabolisms. These patterns include autopoietic structures that maintain their organisation, recursive ones that grow in linear chains or binary-branching trees, and most notably, patterns able to reproduce themselves, duplicating their number at each generation.
翻译:动态单位出现的解释模式必须展示新兴结构,这些结构:(1) 时间保存自己(2) 自我生产,(3) 复制时容忍一定数量的变异。为了应对这一挑战,我们在此引入了混合化学,即基于最小计算模式(称为混合逻辑 ) 的演算人工化学。这个体系的动态由为数不多的规则组成,具有初级的塔布拉拉马萨状态,并具有复制自然资源限制的保存法特征。我们的实验显示,这一动态系统的单一运行,没有外部干预,发现了一系列广泛的新出现模式。所有这些结构都依赖于从环境中获取基本成分,并在一个与生物新陈代谢非常相似的进程中将其分解。这些模式包括维持其组织的自生结构、在线性链或双层树中生长的循环结构,以及最明显的是能够复制自己、复制每代中数量的模式。