New emphasis has been given to complexity, networks, and patterns of organisation, leading to a novel kind of 'systemic' thinking. This volume integrates the ideas, models, and theories underlying the systems view of life into a single coherent framework. Taking a broad sweep through history and across scientific disciplines, the authors examine the appearance of key concepts such as autopoiesis, dissipative structures, social networks, and a systemic understanding of evolution. The implications of the systems view of life for health care, management, and our global ecological and economic crises are also discussed. Written primarily for undergraduates, it is also essential reading for graduate students and researchers interested in understanding the new systemic conception of life and its implications for a broad range of professions - from economics and politics to medicine, psychology and law.

    However, figuring out how to tell it interactively - can be challenging. This work provides examples of contemporary games that rely on different technologies - and learn the storytelling lessons to be garnered from each of the past methodologies.

    By reconstructing authentic, complex AI programs using state-of-the-art Common Lisp, the book teaches students and professionals how to build and debug robust practical programs, while demonstrating superior programming style and important AI concepts. The author strongly emphasizes the practical performance issues involved in writing real working programs of significant size. Chapters on troubleshooting and efficiency are included, along with a discussion of the fundamentals of object-oriented programming and a description of the main CLOS functions. This volume is an excellent text for a course on AI programming, a useful supplement for general AI courses and an indispensable reference for the professional programmer.

    Brian Arthur puts forth the first complete theory of the origins and evolution of technology, in a major work that achieves for the invention of new technologies what Darwin’s theory achieved for the emergence of new species. Brian Arthur is a pioneer of complexity theory and the discoverer of the highly influential "theory of increasing returns," which took Silicon Valley by storm, famously explaining why some high-tech companies achieve breakaway success. Now, in this long-awaited and ground-breaking book, he solves the great outstanding puzzle of technology—where do transformative new technologies come from?—putting forth the first full theory of how new technologies emerge and offering a definitive answer to the mystery of why some cultures—Silicon Valley, Cambridge, England in the 1920s—are so extraordinarily inventive. He has discovered that rather than springing from insight moments of individual genius, new technologies arise in a process akin to evolution. Technology evolves by creating itself out of itself, much as a coral reef builds itself from activities of small organisms. Drawing on a wealth of examples, from the most ancient to cutting-edge inventions of today, Arthur takes readers on a delightful intellectual journey, bringing to life the wonders of this process of technological evolution. The Nature of Technology is the work of one of our greatest thinkers at the top of his game, composing a classic for our times that is sure to generate wide acclaim.

    We've even delegated life-and-death decisions to algorithms--decisions once made by doctors, pilots, and judges. In his new book, Kartik Hosanagar surveys the brave new world of algorithmic decision-making and reveals the potentially dangerous biases they can give rise to as they increasingly run our lives. He makes the compelling case that we need to arm ourselves with a better, deeper, more nuanced understanding of the phenomenon of algorithmic thinking. And he gives us a route in, pointing out that algorithms often think a lot like their creators--that is, like you and me.Hosanagar draws on his experiences designing algorithms professionally--as well as on history, computer science, and psychology--to explore how algorithms work and why they occasionally go rogue, what drives our trust in them, and the many ramifications of algorithmic decision-making. He examines episodes like Microsoft's chatbot Tay, which was designed to converse on social media like a teenage girl, but instead turned sexist and racist; the fatal accidents of self-driving cars; and even our own common, and often frustrating, experiences on services like Netflix and Amazon. A Human's Guide to Machine Intelligence is an entertaining and provocative look at one of the most important developments of our time and a practical user's guide to this first wave of practical artificial intelligence.

    Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords?In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures

    Turing Mathematician Alan Turing invented an imaginary computer known as the Turing Machine; in an age before computers, he explored the concept of what it meant to be "computable," creating the field of computability theory in the process, a foundation of present-day computer programming.The book expands Turing's original 36-page paper with additional background chapters and extensive annotations; the author elaborates on and clarifies many of Turing's statements, making the original difficult-to-read document accessible to present day programmers, computer science majors, math geeks, and others.Interwoven into the narrative are the highlights of Turing's own life: his years at Cambridge and Princeton, his secret work in cryptanalysis during World War II, his involvement in seminal computer projects, his speculations about artificial intelligence, his arrest and prosecution for the crime of "gross indecency," and his early death by apparent suicide at the age of 41.

    But until now, there has been no real manual on how to use Python for a variety of hacking tasks. You had to dig through forum posts and man pages, endlessly tweaking your own code to get everything working. Not anymore.Gray Hat Python explains the concepts behind hacking tools and techniques like debuggers, trojans, fuzzers, and emulators. But author Justin Seitz goes beyond theory, showing you how to harness existing Python-based security tools - and how to build your own when the pre-built ones won't cut it.You'll learn how to:Automate tedious reversing and security tasks Design and program your own debugger Learn how to fuzz Windows drivers and create powerful fuzzers from scratch Have fun with code and library injection, soft and hard hooking techniques, and other software trickery Sniff secure traffic out of an encrypted web browser session Use PyDBG, Immunity Debugger, Sulley, IDAPython, PyEMU, and more The world's best hackers are using Python to do their handiwork. Shouldn't you?

    Mitchell covers the field of machine learning, the study of algorithms that allow computer programs to automatically improve through experience and that automatically infer general laws from specific data.

    For his own reasons he still remains anonymous, the hypnotic self-help elite must be ruffled! They don’t want this stuff getting out! The Rogue Hypnotist is a top UK clinical hypnotherapist and Advanced NLP expert. He has a very good success rate indeed with his client’s and he wants to share the tricks that work with you! He helps his client’s in 1 session only at a very reasonable rate. They leave with a big smile on their faces. Police officers, multimillionaire’s even TV celebs have sought his help; now he wants to help YOU! The sequel to ‘How to hypnotise anyone,’ the number 1 best seller on hypnosis on Amazon.com and .co.uk is here! ‘Mastering hypnotic language,’ awaits you!!! You can now take your hypnotic mastery up to the next level! In book 1 you learnt how to hypnotise anyone using words alone. Now you will learn how to use words with such precision that your total hypnotic power is assured! The Rogue Hypnotist is giving away almost for free all the ‘language patterns’ that work as opposed to all the junk being sold out that that won’t do anything to anyone. Learning hypnosis should be easy and fun! The hypnosis bag of magic tricks that you can expect to effortlessly learn and put into practise are… 1. The specific language that will induce trance and hypnosis in anyone. 2. Why words beginning in RE are hypnotic! 3. Why you SHOULD use PMR (Progressive Muscle Relaxation) with a script showing just how to do so. 4. How to dissociate the conscious and unconscious minds. Script provided! 5. What ‘colour feelings’ are and how to use them in hypnosis. 6. The secrets of ‘hidden code’ hypnosis. 7. How to use ‘hypnotic negations’ properly and why they work. 8. The amazing expose of how the unconscious reveals the truth through ‘reverse speech.’ 9. A powerful and much more advanced ‘hypnotic mind model,’ that will give you far greater understanding of how the mind works than 99% of mental health care professionals, helping you hypnotise anyone with flair. 10. What the best ‘temporal and spatial’ language predicates to use in hypnosis are. 11. Exactly how to use language to dig out specifics, to find the missing pieces and stop yourself being influenced against your will. 12. How to use hypnotic assumptions and nominalisations and which ones work best. 13. How to specifically and expertly use artfully vague hypnotic language. 14. What hyperbolic words and hypnotic poetry is. 15. The specifics of ‘hypnotic languaging.’ 16. A knowledge of associational networks and artful ambiguity. 17. The 100% fail proof formula to create your own hypnotic deepeners! It’s easier than you think! And you get a free bonus – ‘The Silly Deepener!’ 18. An embedded commands induction PLUS the specific ‘embeds’ that induce trance in any conversation. You will learn TRUE conversational hypnosis that works including how to describe a state to elicit it! 19. A step by step description of the precise way to create a ‘symbolic deepener’ with full script provided. 20. Your special BONUS – ‘The Unicorn Deepener’ and much, much more! The Rogue Hypnotist is practically giving this away so that YOU will have by end of the book more hypnotic ability than 99% of so-called hypnotists out there! That’s my promise to you.

    Nobel laureate Murray Gell-Mann offers a uniquely personal and unifying vision of the relationship between the fundamental laws of physics and the complexity and diversity of the natural world.

    But many people use data in ways they don't even understand, meaning they aren't getting the most from it. Bayesian Statistics the Fun Way will change that.This book will give you a complete understanding of Bayesian statistics through simple explanations and un-boring examples. Find out the probability of UFOs landing in your garden, how likely Han Solo is to survive a flight through an asteroid shower, how to win an argument about conspiracy theories, and whether a burglary really was a burglary, to name a few examples.By using these off-the-beaten-track examples, the author actually makes learning statistics fun. And you'll learn real skills, like how to:- How to measure your own level of uncertainty in a conclusion or belief- Calculate Bayes theorem and understand what it's useful for- Find the posterior, likelihood, and prior to check the accuracy of your conclusions- Calculate distributions to see the range of your data- Compare hypotheses and draw reliable conclusions from themNext time you find yourself with a sheaf of survey results and no idea what to do with them, turn to Bayesian Statistics the Fun Way to get the most value from your data.

    Unlike traditional empirical psychology, it is more oriented toward the how than the what. An experiment in mind design is more likely to be an attempt to build something and make it work--as in artificial intelligence--than to observe or analyze what already exists. Mind design is psychology by reverse engineering.When Mind Design was first published in 1981, it became a classic in the then-nascent fields of cognitive science and AI. This second edition retains four landmark essays from the first, adding to them one earlier milestone (Turing's Computing Machinery and Intelligence) and eleven more recent articles about connectionism, dynamical systems, and symbolic versus nonsymbolic models. The contributors are divided about evenly between philosophers and scientists. Yet all are philosophical in that they address fundamental issues and concepts; and all are scientific in that they are technically sophisticated and concerned with concrete empirical research.ContributorsRodney A. Brooks, Paul M. Churchland, Andy Clark, Daniel C. Dennett, Hubert L. Dreyfus, Jerry A. Fodor, Joseph Garon, John Haugeland, Marvin Minsky, Allen Newell, Zenon W. Pylyshyn, William Ramsey, Jay F. Rosenberg, David E. Rumelhart, John R. Searle, Herbert A. Simon, Paul Smolensky, Stephen Stich, A.M. Turing, Timothy van Gelder

    With this practical book, you’ll learn how to design and implement a graph database that brings the power of graphs to bear on a broad range of problem domains. Whether you want to speed up your response to user queries or build a database that can adapt as your business evolves, this book shows you how to apply the schema-free graph model to real-world problems.Learn how different organizations are using graph databases to outperform their competitors. With this book’s data modeling, query, and code examples, you’ll quickly be able to implement your own solution.Model data with the Cypher query language and property graph modelLearn best practices and common pitfalls when modeling with graphsPlan and implement a graph database solution in test-driven fashionExplore real-world examples to learn how and why organizations use a graph databaseUnderstand common patterns and components of graph database architectureUse analytical techniques and algorithms to mine graph database information

    A step-by-step visual journey through the mathematics of neural networks, and making your own using Python and Tensorflow.