Instead, ants decide what to do based on the rate, rhythm, and pattern of individual encounters and interactions--resulting in a dynamic network that coordinates the functions of the colony. Ant Encounters provides a revealing and accessible look into ant behavior from this complex systems perspective.Focusing on the moment-to-moment behavior of ant colonies, Deborah Gordon investigates the role of interaction networks in regulating colony behavior and relations among ant colonies. She shows how ant behavior within and between colonies arises from local interactions of individuals, and how interaction networks develop as a colony grows older and larger. The more rapidly ants react to their encounters, the more sensitively the entire colony responds to changing conditions. Gordon explores whether such reactive networks help a colony to survive and reproduce, how natural selection shapes colony networks, and how these structures compare to other analogous complex systems. Ant Encounters sheds light on the organizational behavior, ecology, and evolution of these diverse and ubiquitous social insects.

    One of the foremost workers in this multidisciplinary field is Daniel Dennett. This book brings together his essays on the philosphy of mind, artificial intelligence, and cognitive ethology that appeared in inaccessible journals from 1984 to 1996. Highlights include "Can Machines Think?", "The Unimagined Preposterousness of Zombies", "Artificial Life as Philosophy", and "Animal Consciousness: What Matters and Why". Collected in a single volume, the essays are now available to a wider audience.

    When we use consumer products from Google, Microsoft, Facebook, Apple, or Baidu, we are often interacting with a deep learning system. In this volume in the MIT Press Essential Knowledge series, computer scientist John Kelleher offers an accessible and concise but comprehensive introduction to the fundamental technology at the heart of the artificial intelligence revolution.Kelleher explains that deep learning enables data-driven decisions by identifying and extracting patterns from large datasets; its ability to learn from complex data makes deep learning ideally suited to take advantage of the rapid growth in big data and computational power. Kelleher also explains some of the basic concepts in deep learning, presents a history of advances in the field, and discusses the current state of the art. He describes the most important deep learning architectures, including autoencoders, recurrent neural networks, and long short-term networks, as well as such recent developments as Generative Adversarial Networks and capsule networks. He also provides a comprehensive (and comprehensible) introduction to the two fundamental algorithms in deep learning: gradient descent and backpropagation. Finally, Kelleher considers the future of deep learning—major trends, possible developments, and significant challenges.

    Guiding us through the strange and fascinating workings of the subatomic realm to create a new model of human consciousness, the author addresses enduring philosophical questions. Does the new physics provide a basis by which our consciousness might continue beyond death? How does the material world (for instance, ugly inner cities) impinge upon our sense of self? Is there a subatomic wellspring from which our creativity, our empathy with others, and our feelings of unity with the inanimate world originate?Most important, Zohar shows how the vitality of the new physics combats the alienation and fragmentation of twentieth-century life, and replaces it with a model of reality in which the universe itself may possess a type of consciousness, of which human consciousness is one expression.

    Johnson-Bennett shares real cases to illustrate various problems and explains how she arrives at an appropriate solution through behavior modification. Her method requires a positive approach to correcting the behavior rather than punishment. She also uses interactive toys, which she believes helps not only to correct the behavior problem, but also to put the cat/owner relationship back in sync.

    Shirer's new book - written in his ninth decade - explores the passionate, highly charged, and extraordinary lives of Leo and Sonya Tolstoy. It is a compelling illumination both of the nature of genius and of the universal problems of love, sex, and marriage - themes that Tolstoy played out in his great fiction and that haunted him in his tangled domestic life. Rich in anecdotes, wise, full of sweeping history, and imbued with Shirer's profound knowledge of literature and life, Love and Hatred ranks beside such works as Robert Massie's Nicholas and Alexandra and Nigel Nicolson's Portrait of a Marriage as a masterly, intuitive, and sympathetic exploration of the love/hate relationship between two famous, bigger-than-life people. Beginning in 1862, when Tolstoy committed the blunder of asking his young bride to read his diaries of his bachelor life so there should be no secrets between them, and ending with his tragic flight from home (and marriage) in 1910 while the whole world waited for news of him, Love and Hatred tells the story of a great romance between two people who could live neither together nor apart - a romance that exhausted and obsessed them both, and that forms the basis for much of Tolstoy's work. The final book of William L. Shirer's long and brilliant career, it is - appropriately - a masterly re-creation of a time, of two extraordinary people, and of the very nature of love, marriage, and old age.

    This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work. This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.

    

    In this book, William Cook takes readers on a mathematical excursion, picking up the salesman's trail in the 1800s when Irish mathematician W. R. Hamilton first defined the problem, and venturing to the furthest limits of today's state-of-the-art attempts to solve it. He also explores its many important applications, from genome sequencing and designing computer processors to arranging music and hunting for planets.In Pursuit of the Traveling Salesman travels to the very threshold of our understanding about the nature of complexity, and challenges you yourself to discover the solution to this captivating mathematical problem.

    According to them, “intelligent machines” and big data will free us from work, educate our children, transform our environment, and even make religion more user-friendly. This is the story they’re telling us: that we should stop worrying and love our robot future. But just because you tell a story over and over again doesn’t make it true. Curtis White, one of our most brilliant and perceptive social critics, knows all about the danger of a seductive story, and in We, Robots, he tangles with the so-called thinkers who are convinced that the future is rose-colored and robotically enhanced. With tremendous erudition and a punchy wit, White argues that we must be skeptical of anyone who tries to sell us on technological inevitability. And he gives us an alternative set of stories: taking inspiration from artists as disparate as Sufjan Stevens, Lars von Trier, and François Rabelais, White shows us that by looking to art, we can imagine a different kind of future. No robots required.From the Hardcover edition.

    The self-driving car has been one of the most vaunted technological breakthroughs of recent years. But early promises that these autonomous vehicles would soon be on the roads have proven premature. Alex Davies follows the twists and turns of this story from its origins to today. The story starts with the Defense Advanced Research Projects Agency (DARPA), which was charged with developing a land-based equivalent to the drone, a vehicle that could operate in war zones without risking human lives. DARPA issued a series of three “Grand Challenges” that attracted visionaries, many of them students and amateurs, who took the technology from Jetsons-style fantasy to near-reality. The young stars of the Challenges soon connected with Silicon Valley giants Google and Uber, intent on delivering a new way of driving to the civilian world. Soon the automakers joined the quest, some on their own, others in partnership with the tech titans. But as road testing progressed, it became clear that the challenges of driving a car without human assistance were more formidable than anticipated. Davies profiles the industry’s key players from the early enthusiasm of the DARPA days to their growing awareness that while this spin on artificial intelligence isn’t yet ready for rush-hour traffic, driverless cars are poised to remake how the world moves. Driven explores this exciting quest to transform transportation and change our lives.

    Authors Drew Conway and John Myles White help you understand machine learning and statistics tools through a series of hands-on case studies, instead of a traditional math-heavy presentation.Each chapter focuses on a specific problem in machine learning, such as classification, prediction, optimization, and recommendation. Using the R programming language, you'll learn how to analyze sample datasets and write simple machine learning algorithms. "Machine Learning for Hackers" is ideal for programmers from any background, including business, government, and academic research.Develop a naive Bayesian classifier to determine if an email is spam, based only on its textUse linear regression to predict the number of page views for the top 1,000 websitesLearn optimization techniques by attempting to break a simple letter cipherCompare and contrast U.S. Senators statistically, based on their voting recordsBuild a "whom to follow" recommendation system from Twitter data

    Collected here to keep your wits sharp, The Best Brain Teasers of All Time features the cleverest brain teasers from around the world and throughout history.The Best Brain Teasers of All Time gives you hours of fun-filled entertainment with brain teasers that develop your problem-solving skills in math, logic, and wordplay. Organized as an integrated challenge, these brain teasers build in momentum as they increase in difficulty from classic nursery rhymes to the riddle of the sphinx.The Best Brain Teasers of All Time puts your mind to the test with: 125 Brain Teasers that require no special skills to solve. Plus, each question comes with an optional clue in case you get stumped and a handy answer key in the back to test yourself or play with friends Brain Teasers for Every Level that cater to beginners and advanced masterminds alike, with brain teasers organized by level of difficulty to improve your skills as you move forward Hints of History that provide fun facts and background information for every brain teaser Get ready to sharpen your wit with every “aha” moment. The Best Brain Teasers of All Time is a go-to source for timeless fun and mind-blowing challenges.

    Intended for developers who are already familiar with the Apex language, and experienced Java and C# developers who are moving to Apex, this book starts where the Force.com documentation leaves off. Instead of trying to cover all of the features of the platform, Advanced Apex programming focuses entirely on the Apex language and core design patterns. You’ll learn how to truly think in Apex – to embrace limits and bulk patterns. You’ll see how to develop architectures for efficient and reliable trigger handling, and for asynchronous operations. You’ll discover that best practices differ radically depending on whether you are building software for a specific organization or for a managed package. And you’ll find approaches for incorporating testing and diagnostic code that can dramatically improve the reliability and deployment of Apex software, and reduce your lifecycle and support costs. Based on his experience both as a consultant and as architect of a major AppExchange package, Dan Appleman focuses on the real-world problems and issues that are faced by Apex developers every day, along with the obscure problems and surprises that can sneak up on you if you are unprepared.

    These days, linger over a Web page selling lamps, and they will turn up at the advertising margins as you move around the Internet, reminding you, tempting you to make that purchase. Search engines such as Google can now look deep into the data on the Web to pull out instances of the words you are looking for. And there are pages that collect and assess information to give you a snapshot of changing political opinion. These are just basic examples of the growth of Web intelligence, as increasingly sophisticated algorithms operate on the vast and growing amount of data on the Web, sifting, selecting, comparing, aggregating, correcting; following simple but powerful rules to decide what matters. While original optimism for Artificial Intelligence declined, this new kind of machine intelligence is emerging as the Web grows ever larger and more interconnected.Gautam Shroff takes us on a journey through the computer science of search, natural language, text mining, machine learning, swarm computing, and semantic reasoning, from Watson to self-driving cars. This machine intelligence may even mimic at a basic level what happens in the brain.