Computability and complexity theory are two central areas of research in theoretical computer science. This book provides a systematic, technical development of "algorithmic randomness" and complexity for scientists from diverse fields.

The interplay between computability and randomness has been an active area of research in recent years, reflected by ample funding in the USA, numerous workshops, and publications on the subject. The complexity and the randomness aspect of a set of natural numbers are closely related. Traditionally, computability theory is concerned with the complexity aspect. However, computab...(展开全部)

The interplay between computability and randomness has been an active area of research in recent years, reflected by ample funding in the USA, numerous workshops, and publications on the subject. The complexity and the randomness aspect of a set of natural numbers are closely related. Traditionally, computability theory is concerned with the complexity aspect. However, computab...(展开全部)

This book provides a challenging and stimulating introduction to the contemporary topics of complexity and criticality, and explores their common basis. Criticality refers to the behaviour of extended systems at a phase transition where scale invariance prevails; the many constituent microscopic parts bringing about macroscopic phenomena that cannot be understood by considering...(展开全部)

Amazon.com "Chance governs all," said Milton, but he was writing about hell, not statistical probability. In the modern world, we assume that Milton's hell is everywhere--that is, that fate is best described in terms of statistics, odds, risks, and randomness. But most people, even many scientists, find probability difficult to understand and often counter to common sense. Math...(展开全部)

Amazon.com "Chance governs all," said Milton, but he was writing about hell, not statistical probability. In the modern world, we assume that Milton's hell is everywhere--that is, that fate is best described in terms of statistics, odds, risks, and randomness. But most people, even many scientists, find probability difficult to understand and often counter to common sense. Math...(展开全部)

布莱恩·阿瑟 著名经济学家，研究经济正反馈机制的先驱。 在加州大学伯克利分校获得经济学硕士学位和运筹学博士学位，37岁就成为斯坦福大学*年轻的经济学教授。 1987年获得“古根海姆奖”，1990年获得“熊比特奖”。 1987年进入圣塔菲研究所，投身于跨学科的复杂性科学领域。1988年，主持圣塔菲的研究项目。他是圣塔菲的元老级人物，也是复杂性科学的奠基人。他因成绩突出而荣获首届“拉格朗日奖”。 对技术与科学、经济之间的关系，他见解独特，是一位技术思想家。 2014年，由湛庐文化引进出版其著作《技术的本质》（The Nature of Technology: What It Is and How It Evolves）。

"Data Structure and Algorithmic Thinking with Python" is designed to give a jump-start to programmers, job hunters and those who are appearing for exams. All the code in this book are written in Python. It contains many programming puzzles that not only encourage analytical thinking, but also prepares readers for interviews. This book, with its focused and practical approach, c...(展开全部)