元胞自动机是一种时间、空间、状态都离散的动力学模型，是非线性科学的一种重要研究方法，特别适合于复杂系统时空演化过程的动态模拟研究。本书共分7章。前两章对元胞自动机的发展历程、理论基础和基本演化规则做了概论；后5章从客观过程的并行性出发，以物理系统的守恒定律为基础，建立了宏观物理学与微观离散动力学之间的联系，构造了平衡和非平衡系统相关的元胞自动机模型。本书论述深入浅出，并附有大量习题，非常适合于用作物理学领域的研究生教材，同时可供从事复杂系统模拟和计算机科学的研究人员参考。

本书描述了历史上从中国西周到乌干达北部的伊克族等二十多个由简单社会进化到相对复杂的社会后却走向崩溃的案例，并回顾了两千多年来后人对于这些崩溃现象的解释。作者还阐释了复杂社会的性质，并通过在社会政治复杂化领域具有广泛代表性的罗马文明、玛雅文明、查科文明从兴起到衰落的详细研究，为理解崩溃现象提供了一个新的视角，那就是从社会复杂化投资的边际回报（即每增加一个单位的劳动投入所带来的产量增加的回报）来判断一个社会是处于向更高阶段发展的复杂化进程中，还是正走向相反的崩溃进程。

An introductory text in nonlinear dynamics and chaos, emphasizing applications in several areas of science, which include vibrations, biological rhythms, insect outbreaks, and genetic control systems. Contains a rich selection of illustrations, with many exercises and examples. Softcover.

The synchronized flashing of fireflies at night. The spiraling patterns of an aggregating slime mold. The anastomosing network of army-ant trails. The coordinated movements of a school of fish. Researchers are finding in such patterns - phenomena that have fascinated naturalists for centuries - a fertile new approach to understanding biological systems: the study of self-organization. This book, a primer on self-organization in biological systems for students and other enthusiasts, introduces readers to the basic concepts and tools for studying self-organization and then examines numerous examples of self-organization in the natural world. Self-organization refers to diverse pattern formation processes in the physical and biological world, from sand grains assembling into rippled dunes to cells combining to create highly structured tissues to individual insects working to create sophisticated societies. What these diverse systems hold in common is the proximate means by which they acquire order and structure. In self-organizing systems, pattern at the global level emerges solely from interactions among lower-level components. Remarkably, even very complex structures result from the iteration of surprisingly simple behaviors performed by individuals relying on only local information. This striking conclusion suggests important lines of inquiry: to what degree is environmental rather than individual complexity responsible for group complexity? To what extent have widely differing organisms adopted similar, convergent strategies of pattern formation? How, specifically, has natural selection determined the rules governing interactions within biological systems? Broad in scope, thorough yet accessible, this book is a self-contained introduction to self-organization and complexity in biology - a field of study at the forefront of life sciences research.

From the Internet to networks of friendship, disease transmission, and even terrorism, the concept - and the reality - of networks has come to pervade modern society. But what exactly is a network? What different types of networks are there? Why are they interesting, and what can they tell us? In recent years, scientists from a range of fields - including mathematics, physics, computer science, sociology, and biology - have been pursuing these questions and building a new 'science of networks.' This book brings together, for the first time, a set of seminal articles representing research from across these disciplines. It is an ideal sourcebook for the key research in this fast-growing field. The book is organized into four sections, each preceded by an editors' introduction summarizing its contents and general theme. The first section sets the stage by discussing some of the historical antecedents of contemporary research in the area. From there the book moves to the empirical side of the science of networks before turning to the foundational modeling ideas that have been the focus of much subsequent activity. The book closes by taking the reader to the cutting edge of network science - the relationship between network structure and system dynamics. From network robustness to the spread of disease, this section offers a potpourri of topics on this rapidly expanding frontier of the new science.

Are all film stars linked to Kevin Bacon? Why do the stock markets rise and fall sharply on the strength of a vague rumour? How does gossip spread so quickly? Are we all related through six degrees of separation? There is a growing awareness of the complex networks that pervade modern society. We see them in the rapid growth of the Internet, the ease of global communication, the swift spread of news and information, and in the way epidemics and financial crises develop with startling speed and intensity. This introductory book on the new science of networks takes an interdisciplinary approach, using economics, sociology, computing, information science and applied mathematics to address fundamental questions about the links that connect us, and the ways that our decisions can have consequences for others.

过去十年来，现代社会中复杂的连通性向公众展现出与日俱增的魅力。这种连通性在许多方面都有体现并发挥着强大的作用，包括互联网的快速成长、全球通信的便捷，以及新闻与信息（及传染病与金融危机）以惊人的速度与强度传播的能力。这种现象涉及网络、动机和人们的聚合行为。网络将人们的行为联系起来，使得每个人的决定可能对他人产生微妙的后果。
本书是本科生的入门教材，同时也适合希望进入相关领域的高层次读者。它从交叉学科的角度出发，综合运用经济学、社会学、计算与信息科学以及应用数学的有关概念与方法，考察网络行为原理及其效应机制。以深入浅出的方式描述了在网络的作用下正在浮现与发展起来的一些交叉学科领域，讨论了社会、经济和技术领域相互联系的若干基本问题。本书是一本带你跨入信息科学和社会科学交叉领域研究之门的优秀参考书。

This text is intended for the general reader who is interested in science. The author is a physicist who is well known for his development of the property called "self organized criticality", a property or phenomenon that lies at the heart of large dynamical systems. It can be used to analyze systems that are complicated, and which are part of the new science of complexity. It is a unifying concept that can be used to study phenomena in fields as diverse as economics, astronomy, the earth sciences, and physics. The author discusses his discovery of self organized criticality, its relation to the world of classical physics computer simulations and experiments which aid scientists' understanding of the property and the relation of the subject to popular areas such as fractal geometry and power laws cellular automata, and a wide range of practical applications.

在纷繁的社会生活中，个体的行为是无法预知的，但是，当个体数量达到一定程度时，群体的行为反而表现得有章可循，于杂乱中显现秩序和稳定。这是为什么呢？
围绕这一问题，作者从统计物理、生物化学等自然科学中探寻其中的缘由，发现了自然与社会之间奇妙的结合点，以及它们共同的法则。从细菌生长的形态到交通流的运行，从流体相变到政治结盟，从电脑网络到市场交易，等等，莫不于纷繁多样中遵从一致的奇妙规则。
结论或许令人充满遐想，论证的过程却平易生动。作者小心翼翼地择取例证，谨慎地驱遣词句，以所有人都看得懂的方式，讲述各门类的知识与道理，实属少见。

《进化动力学:探索生命的方程》一书阐释了生命进化所遵循的数学原理。进化动力学主要涉及复制、突变、选择、随机漂变和空间运动等过程。《进化动力学:探索生命的方程》结合生物学理论和数学语言对这些问题进行了论述。开篇简要介绍了与进化相关的基本概念、种群动力学基本模型以及准种理论；然后介绍进化动力学基本研究方法及其应用，分别就合作行为、HIV、病原体、癌症以及人类语言的进化机制展开讨论，其中所涉及的研究方法主要有进化博弈理论、囚徒困境模型、进化图论、网络博弈等。
《进化动力学:探索生命的方程》语言简洁有力，论述生动有趣。虽然书中涉及大量的数学方法，但是，读者只需具备一定的数学基础，就不会感到晦涩枯燥。该书适合于具有生物学、数学以及具有其他相关学科背景的读者阅读。

We know, down to the tiniest details, the molecular structure of the human immunodeficiency virus (HIV). Yet despite this tremendous accomplishment, and despite other remarkable advances in our understanding of individual viruses and cells of the immune system, we still have no agreed understanding of the ultimate course and variability of the pathogenesis of AIDS. Gaps in our understanding like these impede our efforts towards developing effective therapies and preventive vaccines. Martin Nowak and Robert M May describe the emerging field of theoretical immunology in this accessible and well- written text. Using mathematical modelling techniques, the authors set out their ideas about how populations of viruses and populations of immune system cells may interact in various circumstances, and how infectious diseases spread within patients. They explain how this approach to understanding infectious diseases can reveal insights into the dynamics of viral and other infections, and the interactions between infectious agents and immune responses. The book is structured around the examples of HIV/AIDS and Hepatitis B virus, although the approaches described will be more widely applicable. The authors use mathematical tools to uncover the detailed dynamics of the infection and the effects of antiviral therapy. Models are developed to describe the emergence of drug resistance, and the dynamics of immune responses, viral evolution, and mutation. The practical implications of this work for optimisation of the design of therapy and vaccines are discussed. The book concludes with a glance towards the future of this fascinating, and potentially highly useful, field of study.

Physics and computer science genius Stephen Wolfram, whose Mathematica computer language launched a multimillion-dollar company, now sets his sights on a more daunting goal: understanding the universe. Wolfram lets the world see his work in
, a gorgeous, 1,280-page tome more than a decade in the making. With patience, insight, and self-confidence to spare, Wolfram outlines a fundamental new way of modeling complex systems.

《探索复杂性》内容简介：耗散结构理论由于在社会经济等大范围领域中展现的广阔前景，引起了人们的极大兴趣，与协同论、突变论并称为现代科学方法论的新三论。美国著名作家托夫勒认为，这一理论“可能代表了下一次科学革命”。《探索复杂性》作者之一普利高津因提出这一理论而获得1977年诺贝尔奖，《探索复杂性》的另一作者布鲁塞尔学派主要成员尼科里斯教授，是欧洲著名的物理学家，对发展耗散结构理论做出了杰出的贡献。
书中全面地介绍了以耗散结构理论为代表的进化论物理学的最新成就，着力于打破自然科学各门类之间乃至自然科学与社会科学之间的壁垒，再次点燃科学革命之火。
《探索复杂性》内容新颖、文笔优美、深入浅出，适宜于物理学、化学、数学、生物学、医学、地质学等专业的科学工作者、大专院校师生阅读，也适宜于社会科学工作者和具有中等文化程度的读者阅读。