Taming the Complexity of Evolutionary Dynamics: From Microscopic Models to Schema Theory and Beyond

The study of complex adaptive systems is among the key modern tasks in science. Such systems show radically different behaviours at different scales and in different environments, and mathematical modelling of such emergent behaviour is very difficult, even at the conceptual level. We require a new methodology to study and understand complex, emergent macroscopic phenomena. Coarse graining, a technique that originated in statistical physics, involves taking a system with many microscopic degrees of freedom and finding an appropriate subset of collective variables that offer a compact, computationally feasible description of the system, in terms of which the dynamics looks "natural".

The authors explain the basics of natural and artificial evolutionary dynamics, and offer detailed treatments of the related models of search spaces, population spaces, state spaces, crossover, mutation and selection. The rest of the book is concerned with the mathematical modelling of these aspects of evolutionary dynamics using the coarse graining technique, and with analysis of the subsequent models.

This book is a significant contribution to the theory of artificial evolutionary systems, and will be key reading for theoreticians in computer science, artificial intelligence and engineering. While the insights into how complexity can be tamed will be valuable reading for biologists and physicists engaged with the theory of natural evolutionary systems.

複雜適應系統的研究是科學中的重要任務之一。這些系統在不同的尺度和環境下展現出截然不同的行為，即使在概念層面上，對這種新興行為的數學建模也非常困難。我們需要一種新的方法論來研究和理解複雜的、新興的宏觀現象。粗粒化是一種起源於統計物理學的技術，它涉及將具有許多微觀自由度的系統，找到一個適當的集體變量子集，以提供對系統的簡潔、可計算的描述，其中動力學看起來“自然”。

作者解釋了自然和人工演化動力學的基礎，並詳細介紹了相關的搜索空間、人口空間、狀態空間、交叉、突變和選擇模型。本書的其餘部分涉及使用粗粒化技術對這些演化動力學方面進行數學建模，以及對後續模型進行分析。

本書對於人工演化系統理論做出了重要貢獻，將成為計算機科學、人工智能和工程學理論家的重要閱讀資料。對於從事自然演化系統理論的生物學家和物理學家來說，對於如何馴服複雜性的洞察力也將是有價值的閱讀材料。

The authors are among the top theoreticians in the field of evolutionary computation. The first author, a physicist, specializes in statistical mechanics, complex systems, multiscale phenomena, and dynamic optimization. The second author, a computer scientist, has over 250 refereed publications on evolutionary computing, artificial intelligence, artificial life, neural networks, biomedical engineering, etc., and his coauthored book "Foundations of Genetic Programming" was the first book to present a theory of genetic programming.

這些作者是進化計算領域中頂尖的理論家之一。第一位作者是一位物理學家，專攻統計力學、複雜系統、多尺度現象和動態優化。第二位作者是一位計算機科學家，擁有超過250篇經過同行評審的論文，涵蓋了進化計算、人工智能、人工生命、神經網絡、生物醫學工程等領域。他與他人合著的書籍《基因編程的基礎》是第一本介紹基因編程理論的書籍。