This essential companion to Chaitin's successful books The Unknowable and The Limits of Mathematics, presents the technical core of his theory of program-size complexity. The two previous volumes are more concerned with applications to meta-mathematics. LISP is used to present the key algorithms and to enable computer users to interact with the authors proofs and discover for themselves how they work. The LISP code for this book is available at the author's Web site together with a Java applet LISP interpreter. "No one has looked deeper and farther into the abyss of randomness and its role in mathematics than Greg Chaitin. This book tells you everything hes seen. Don miss it." John Casti, Santa Fe Institute, Author of Goedel: A Life of Logic.'

From the ancients' first readings of the innards of birds to your neighbor's last bout with the state lottery, humankind has put itself into the hands of chance. Today life itself may be at stake when probability comes into play--in the chance of a false negative in a medical test, in the reliability of DNA findings as legal evidence, or in the likelihood of passing on a deadly congenital disease--yet as few people as ever understand the odds. This book is aimed at the trouble with trying to learn about probability. A story of the misconceptions and difficulties civilization overcame in progressing toward probabilistic thinking, Randomness is also a skillful account of what makes the science of probability so daunting in our own day. To acquire a (correct) intuition of chance is not easy to begin with, and moving from an intuitive sense to a formal notion of probability presents further problems. Author Deborah Bennett traces the path this process takes in an individual trying to come to grips with concepts of uncertainty and fairness, and also charts the parallel path by which societies have developed ideas about chance. Why, from ancient to modern times, have people resorted to chance in making decisions? Is a decision made by random choice fair? What role has gambling played in our understanding of chance? Why do some individuals and societies refuse to accept randomness at all? If understanding randomness is so important to probabilistic thinking, why do the experts disagree about what it really is? And why are our intuitions about chance almost always dead wrong? Anyone who has puzzled over a probability conundrum is struck by the paradoxes and counterintuitive results that occur at a relatively simple level. Why this should be, and how it has been the case through the ages, for bumblers and brilliant mathematicians alike, is the entertaining and enlightening lesson of Randomness.

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.

This book introduces the reader to data science using R and the tidyverse. No prerequisite knowledge is needed in college-level programming or mathematics (e.g., calculus or statistics). The book is self-contained so readers can immediately begin building data science workflows without needing to reference extensive amounts of external resources for onboarding. The contents are targeted for undergraduate students but are equally applicable to students at the graduate level and beyond. The book develops concepts using many real-world examples to motivate the reader. Upon completion of the text, the reader will be able to: Gain proficiency in R programming Load and manipulate data frames, and "tidy" them using tidyverse tools Conduct statistical analyses and draw meaningful inferences from them Perform modeling from numerical and textual data Generate data visualizations (numerical and spatial) using ggplot2 and understand what is being represented An accompanying R package "edsdata" contains synthetic and real datasets used by the textbook and is meant to be used for further practice. An exercise set is made available and designed for compatibility with automated grading tools for instructor use.

Harness the power of randomness (and Python code) to solve real-world problems in fun, hands-on experiments—from simulating evolution to encrypting messages to making machine-learning algorithms! The Art of Randomness is a hands-on guide to mastering the many ways you can use randomized algorithms to solve real programming and scientific problems. You’ll learn how to use randomness to run simulations, hide information, design experiments, and even create art and music. All you need is some Python, basic high school math, and a roll of the dice. Author Ronald T. Kneusel focuses on helping you build your intuition so that you’ll know when and how to use random processes to get things done. You’ll develop a randomness engine (a Python class that supplies random values from your chosen source), then explore how to leverage randomness to: Simulate Darwinian evolution and optimize with swarm-based search algorithms Design scientific experiments to produce more meaningful results by making them truly random Implement machine learning algorithms like neural networks and random forests Use Markov Chain Monte Carlo methods to sample from complex distributions Hide information in audio files and images, generate art, and create music Reconstruct original signals and images from only randomly sampled data Scientific anecdotes and code examples throughout illustrate how randomness plays into areas like optimization, machine learning, and audio signals. End-of-chapter exercises encourage further exploration. Whether you’re a programmer, scientist, engineer, mathematician, or artist, you’ll find The Art of Randomness to be your ticket to discovering the hidden power of applied randomness and the ways it can transform your approach to solving problems, from the technical to the artistic.

This volume, with a Foreword writer Sir Roger Penrose, discusses the foundations of computation in relation to nature. It focuses on two main questions: What is computation?How does nature compute? The contributors are world-renowned experts who have helped shape a cutting-edge computational understanding of the universe. They discuss computation in the world from a variety of perspectives, ranging from foundational concepts to pragmatic models to ontological conceptions and philosophical implications. The volume provides a state-of-the-art collection of technical papers and non-technical essays, representing a field that assumes information and computation to be key in understanding and explaining the basic structure underpinning physical reality. It also includes a new edition of Konrad Zuse's “Calculating Space” (the MIT translation), and a panel discussion transcription on the topic, featuring worldwide experts in quantum mechanics, physics, cognition, computation and algorithmic complexity. The volume is dedicated to the memory of Alan M Turing — the inventor of universal computation, on the 100th anniversary of his birth, and is part of the Turing Centenary celebrations. Contents:Foreword (R Penrose)PrefaceAcknowledgementsIntroducing the Computable Universe (H Zenil)Historical, Philosophical & Foundational Aspects of Computation:Origins of Digital Computing: Alan Turing, Charles Babbage, & Ada Lovelace (D Swade)Generating, Solving and the Mathematics of Homo Sapiens. E Post's Views on Computation (L De Mol)Machines (R Turner)Effectiveness (N Dershowitz & E Falkovich)Axioms for Computability: Do They Allow a Proof of Church's Thesis? (W Sieg)The Mathematician's Bias — and the Return to Embodied Computation (S B Cooper)Intuitionistic Mathematics and Realizability in the Physical World (A Bauer)What is Computation? Actor Model versus Turing's Model (C Hewitt)Computation in Nature & the Real World:Reaction Systems: A Natural Computing Approach to the Functioning of Living Cells (A Ehrenfeucht, J Kleijn, M Koutny & G Rozenberg)Bacteria, Turing Machines and Hyperbolic Cellular Automata (M Margenstern)Computation and Communication in Unorganized Systems (C Teuscher)The Many Forms of Amorphous Computational Systems (J Wiedermann)Computing on Rings (G J Martínez, A Adamatzky & H V McIntosh)Life as Evolving Software (G J Chaitin)Computability and Algorithmic Complexity in Economics (K V Velupillai & S Zambelli)Blueprint for a Hypercomputer (F A Doria)Computation & Physics & the Physics of Computation:Information-Theoretic Teleodynamics in Natural and Artificial Systems (A F Beavers & C D Harrison)Discrete Theoretical Processes (DTP) (E Fredkin)The Fastest Way of Computing All Universes (J Schmidhuber)The Subjective Computable Universe (M Hutter)What Is Ultimately Possible in Physics? (S Wolfram)Universality, Turing Incompleteness and Observers (K Sutner)Algorithmic Causal Sets for a Computational Spacetime (T Bolognesi)The Computable Universe Hypothesis (M P Szudzik)The Universe is Lawless or “Pantôn chrêmatôn metron anthrôpon einai” (C S Calude, F W Meyerstein & A Salomaa)Is Feasibility in Physics Limited by Fantasy Alone? (C S Calude & K Svozil)The Quantum, Computation & Information:What is Computation? (How) Does Nature Compute? (D Deutsch)The Universe as Quantum Computer (S Lloyd)Quantum Speedup and Temporal Inequalities for Sequential Actions (M Żukowski)The Contextual Computer (A Cabello)A Gödel-Turing Perspective on Quantum States Indistinguishable from Inside (T Breuer)When Humans Do Compute Quantum (P Zizzi)Open Discussion Section:Open Discussion on A Computable Universe (A Bauer, T Bolognesi, A Cabello, C S Calude, L De Mol, F Doria, E Fredkin, C Hewitt, M Hutter, M Margenstern, K Svozil, M Szudzik, C Teuscher, S Wolfram & H Zenil)Live Panel Discussion (transcription):What is Computation? (How) Does Nature Compute? (C S Calude, G J Chaitin, E Fredkin, A J Leggett, R de Ruyter, T Toffoli & S Wolfram)Zuse's Calculating Space:Calculating Space (Rechnender Raum) (K Zuse)Afterword to Konrad Zuse's Calculating Space (A German & H Zenil) Readership: Graduate students who are specialized researchers in computer science, information theory, quantum theory and modern philosophy and the general public who are interested in these subject areas. Keywords:Digital Physics;Computational Universe;Digital Philosophy;Reality Theories of the Universe;Models of the World;Thring Computation RandomnessKey Features:The authors are all prominent researchersNo competing titlesState-of-the-art collection of technical papers and non-technical essays

If you have C# knowledge but now want to become truly confident in creating fully functional 2D RPG games with Unity, then this book will show you everything you need to know.