用自动机建模进化计算，揭示自然演化自我迭代的深层机制
Evolutionary Automata and Deep Evolutionary Computation
- 将进化算法抽象为可演化的自动机，实现对进化过程的直接建模
- 支持无限代演化，能表达复杂自适应行为与反馈机制
- 适合研究演化系统本质、自组织与智能涌现的理论学者
自然选择演化是现代科学最引人注目的主题之一，催生了演化算法与演化计算，将自然界中的演化机制应用于计算机求解问题。本文聚焦于演化自动机，这是一种与经典演化算法相类比的演化计算模型。演化自动机提供了一个更完整的演化计算双重模型，类似于抽象自动机（如图灵机）为递归算法及其子集——演化算法提供了更形式化、精确的建模基础。演化自动机是一种能够执行演化计算并可能经历无限代演化的自动机。该模型允许直接模拟演化本身的演化，从而赋予演化自动机和演化计算极强的表达能力。这也暗示了自然演化强大的力量：通过与环境的交互反馈实现自我演化。
原文摘要 · Abstract (English)
Evolution by natural selection, which is one of the most compelling themes of modern science, brought forth evolutionary algorithms and evolutionary computation, applying mechanisms of evolution in nature to various problems solved by computers. In this paper we concentrate on evolutionary automata that constitute an analogous model of evolutionary computation compared to well-known evolutionary algorithms. Evolutionary automata provide a more complete dual model of evolutionary computation, similar like abstract automata (e.g., Turing machines) form a more formal and precise model compared to recursive algorithms and their subset - evolutionary algorithms. An evolutionary automaton is an automaton that evolves performing evolutionary computation perhaps using an infinite number of generations. This model allows for a direct modeling evolution of evolution, and leads to tremendous expressiveness of evolutionary automata and evolutionary computation. This also gives the hint to the power of natural evolution that is self-evolving by interactive feedback with the environment.
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