RANDOMNESS THROUGH COMPUTATION
Some Answers, More Questions
Hector Zenil (ed)
World Scientific ISBN: 978-981-4327-74-9, 981-4327-74-3

Available from: World Scientific/Imperial College Press, Amazon, Amazon UK, Amazon FR, Borders.

Dedicated to the memory of Ray Solomonoff (1926-2009)

Overview: This review volume consists of a set of chapters written by leading scholars, most of them founders of their fields. It explores the connections of Randomness to other areas of scientific knowledge, especially its fruitful relationship to Computability and Complexity Theory, and also to areas such as Probability, Statistics, Information Theory, Biology, Physics, Quantum Mechanics, Learning Theory and Artificial Intelligence.

The contributors cover these topics without neglecting important philosophical dimensions, sometimes going beyond the purely technical to formulate age old questions relating to matters such as determinism and free will.

Covered is the historical perspective, the stochastic side of randomness, including probabilistic deliberations, randomness in connection to the physical world, algorithmic probability, inference and artificial inteligence, computational complexity, randomized algorithms, the string orged connection to computability and applications to othe field

The scope of Randomness Through Computation is novel. Each contributor shares their personal views and anecdotes on the various reasons and motivations which led them to the study of Randomness. Using a question and answer format, they share their visions from their several distinctive vantage points.

Contents:

• Randomness as Circuit Complexity (and the Connection to Pseudorandomness) (E. Allender)
• Randomness Everywhere: My Path to Algorithmic Information Theory (C.S. Calude)
• Metaphysics, Metamathematics and Metabiology (G. Chaitin)
• The Martin-Löf-Chaitin Thesis (J-P. Delahaye)
• Computability, Algorithmic Randomness and Complexity (R.G. Downey)
• Is Randomness Native to Computer Science? Ten Years After (M. Ferbus-Zanda & S. Grigorieff)
• The Impact of Algorithmic Information Theory on Our Current Views (P. Gács)
• Scatter and Regularity Imply Benford's Law... and More (N. Gauvrit & J-P. Delahaye)
• Is Randomness Necessary? (R. Graham)
• Algorithmic Randomness as Foundation of Inductive Reasoning and Artificial Intelligence (M. Hutter)
• Randomness: A Tool for Constructing and Analyzing Computer Programs (A. Kucera)
• Connecting Randomness to Computation (M. Li)
• Some Bridging Results and Challenges in Classical, Quantum and Computational Randomness (G. Longo, C. Palamidessi & T. Paul)
• Randomness, Computability and Information (J.S. Miller)
• Studying Randomness Through Computation (A. Nies)
• Statistical Testing of Randomness: New and Old Procedures (A.L. Rukhin)
• Randomness, Occam’s Razor, AI, Creativity and Digital Physics (J. Schmidhuber)
• Algorithmic Probability — Its Discovery — Its Properties and Application to Strong AI (R.J. Solomonoff)
• From Error-correcting Codes to Algorithmic Information Theory (L. Staiger)
• Uncertainty in Physics and Computation (M.A. Stay)
• Indeterminism and Randomness Through Physics (K. Svozil)
• Probability is a Lot of Logic at Once: If You Don’t Know Which One to Pick, Take ’em All (T. Toffoli)
• Randomness in Algorithms (O. Watanabe)
• The Road to Intrinsic Randomness (S. Wolfram)
• Panel discussion transcription (University of Vermont, Burlington 2007): Is The Universe Random? (C.S. Calude, J. Casti, G.J. Chaitin, Paul Davies, S. Wolfram & K. Svozil)
• Panel discussion transcription (University of Indiana Bloomington 2008): What is Computation? (How) Does Nature Compute? (C.S. Calude, G.J. Chaitin, E. Fredkin, T.J. Leggett, R. de Ruyter, T. Toffoli & S. Wolfram)

Randomness Through Computation is a collection of short essays based on questions presented to some of the most influential scholars in the field. It is a compilation of the views and experiences of some of the visionary pioneers and thinkers in this broad, fundamental and foundational area of intellectual and philosophical inquiry.

Readership: Researchers and students in the broader fields of computer science, mathematics and physics; members of the general public interested in science and in the philosophy of science.

Number of Pages: 440
Type of book: Hardcover
Publication Date: February 2011. Published.