Algorithmic Randomness and Complexity [Paperback]

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.

Exploring the theory of computability and complexity over the real numbers, this book provides a systematic, technical development of algorithmic randomness and complexity for scientists working in diverse fields concerned with theoretical computer science.

This book is concerned with the theory of computability and complexity over the real numbers. This theory was initiated by Turing, Grzegorczyk, Lacombe, Banach and Mazur and has seen rapid growth in recent years.Computability and complexity theory are two central areas of research in theoretical computer science. Until recently, most work in these areas concentrated on problems over discrete structures, but there has been enormous growth of computability theory and complexity theory over the real numbers and other continuous structures, especially incorporating concepts of randomness. One reason for this growth is that more and more computation problems over the real numbers are being dealt with by computer scientists--in computational geometry and in the modeling of dynamical and hybrid systems. Scientists working on these questions come from such diverse fields as theoretical computer science, domain theory, logic, constructive mathematics, computer arithmetic, numerical mathematics, and analysis.An essential resource for all researchers in theoretical computer science, logic, computability theory and complexity.Preface.- Acknowledgments.- Introduction.- I. Background.- Preliminaries.- Computability Theory.- Kolmogorov Complexity of Finite Strings.- Relating Plain and Prefix-Free Complexity.- Effective Reals.- II. Randomness of Sets.- Martin-L?f Randomness.- Other Notions of Effective Randomness.- Algorithmic Randomness and Turing Reducibilƒ*