Does a knowledge of Latin facilitate he learning of computer programming? Does skill in geometry make it easier to learn music? The issue of the transfer of learning from one domain to another is a classic problem in psychology as well as an educational question of great importance, which this ingenious new book sets out to solve through a theory of transfer based on a comprehensive theory of skill acquisition. The question was first studies systematically at the turn of the century by the noted psychologist Edward L. Thorndike, who proposed a theory of transfer based on common elements in two different tasks. Since then, psychologists of different theoretical orientations--verbal learning, gestalt, and information processing--have addressed the transfer question with differing and inconclusive results. Singley and Anderson resurrect Thorndike's theory of identical elements, but in a broader context and from the perspective of cognitive psychology. Making use o a powerful knowledge-representation language, they recast his elements into units of procedural and declarative knowledge in the ACT* theory of skill acquisition. One skill will transfer to another, they argue, to the extent that it involves the same productions or the same declarative precursors. They show that with production rules, ransfer can be localized to specific components--in keeping with Thorndike's theory--and yet still be abstract and mentalistic. The findings of this book have important implications for psychology and the improvement of teaching. They will interest cognitive scientists and educational psychologists, as well as computer scientists interested in artificial intelligence and cognitive modeling.

A comprehensive account of how energy has shaped society throughout history, from pre-agricultural foraging societies through today's fossil fuel–driven civilization.
"I wait for new Smil books the way some people wait for the next 'Star Wars' movie. In his latest book, Energy and Civilization: A History, he goes deep and broad to explain how innovations in humans' ability to turn energy into heat, light, and motion have been a driving force behind our cultural and economic progress over the past 10,000 years.
―Bill Gates, Gates Notes, Best Books of the Year
Energy is the only universal currency; it is necessary for getting anything done. The conversion of energy on Earth ranges from terra-forming forces of plate tectonics to cumulative erosive effects of raindrops. Life on Earth depends on the photosynthetic conversion of solar energy into plant biomass. Humans have come to rely on many more energy flows―ranging from fossil fuels to photovoltaic generation of electricity―for their civilized existence. In this monumental history, Vaclav Smil provides a comprehensive account of how energy has shaped society, from pre-agricultural foraging societies through today's fossil fuel–driven civilization.
Humans are the only species that can systematically harness energies outside their bodies, using the power of their intellect and an enormous variety of artifacts―from the simplest tools to internal combustion engines and nuclear reactors. The epochal transition to fossil fuels affected everything: agriculture, industry, transportation, weapons, communication, economics, urbanization, quality of life, politics, and the environment. Smil describes humanity's energy eras in panoramic and interdisciplinary fashion, offering readers a magisterial overview. This book is an extensively updated and expanded version of Smil's Energy in World History (1994). Smil has incorporated an enormous amount of new material, reflecting the dramatic developments in energy studies over the last two decades and his own research over that time.

What does everyone in the modern world need to know? Renowned psychologist Jordan B. Peterson's answer to this most difficult of questions uniquely combines the hard-won truths of ancient tradition with the stunning revelations of cutting-edge scientific research.
Humorous, surprising, and informative, Dr. Peterson tells us why skateboarding boys and girls must be left alone, what terrible fate awaits those who criticize too easily, and why you should always pet a cat when you meet one on the street.
What does the nervous system of the lowly lobster have to tell us about standing up straight (with our shoulders back) and about success in life? Why did ancient Egyptians worship the capacity to pay careful attention as the highest of gods? What dreadful paths do people tread when they become resentful, arrogant, and vengeful? Dr. Peterson journeys broadly, discussing discipline, freedom, adventure, and responsibility, distilling the world's wisdom into 12 practical and profound rules for life. 12 Rules for Life shatters the modern commonplaces of science, faith, and human nature while transforming and ennobling the mind and spirit of its listeners.

Why have people from different cultures and eras formulated myths and stories with similar structures? What does this similarity tell us about the mind, morality, and the structure of the world itself? Maps of Meaning offers a provocative new hypothesis that explores the connection between what modern neuropsychology tells us about the brain and what rituals, myths and religious stories have long narrated. Drawing insights from the worlds of neuropsychology, cognitive science, and Freudian and Jungian approaches to mythology and narrative, Jordan B. Peterson argues that myths and religious stories have a structure determined by the nature of the mind, and play a key role in the regulation of human emotions.
Ambitious in scope and daring in its exploration of ideas, Maps of Meaning presents a rich theory that makes the wisdom and meaning of myth accessible to the critical modern mind.</P>

Keith Johnstone's involvement with the theatre began when George Devine and Tony Richardson, artistic directors of the Royal Court Theatre, commissioned a play from him. This was in 1956. A few years later he was himself Associate Artistic Director, working as a play-reader and director, in particular helping to run the Writers' Group. The improvisatory techniques and exercises evolved there to foster spontaneity and narrative skills were developed further in the actors' studio then in demonstrations to schools and colleges and ultimately in the founding of a company of performers, called The Theatre Machine. Divided into four sections, 'Status', 'Spontaneity', 'Narrative Skills', and 'Masks and Trance', arranged more or less in the order a group might approach them, the book sets out the specific techniques and exercises which Johnstone has himself found most useful and most stimulating. The result is both an ideas book and a fascinating exploration of the nature of spontaneous creativity.

"A dizzying display of intellect and wild imaginings by Moravec, a world-class roboticist who has himself developed clever beasts . . . Undeniably, Moravec comes across as a highly knowledgeable and creative talent--which is just what the field needs".--Kirkus Reviews.

Effective communication is an essential component of professional success, a stable family life and personal happiness. The abilty to be assertive is a major part of communication. This step-by-step guide uses cognitive-behavioural techniques to help the reader suffering from assertiveness problems to set realistic personal boundaries and transform interpersonal styles. real-life examples, checklists and exercises are supplemented with support and encouragement.

An examination of metaphor in poetry as a microcosm of the human imagination—a way to understand the mechanisms of creativity.
In The Spider's Thread, Keith Holyoak looks at metaphor as a microcosm of the creative imagination. Holyoak, a psychologist and poet, draws on the perspectives of thinkers from the humanities—poets, philosophers, and critics—and from the sciences—psychologists, neuroscientists, linguists, and computer scientists. He begins each chapter with a poem—by poets including Samuel Taylor Coleridge, Sylvia Plath, Walt Whitman, Emily Dickinson, Robert Frost, Theodore Roethke, Du Fu, William Butler Yeats, and Pablo Neruda—and then widens the discussion to broader notions of metaphor and mind.
Holyoak uses Whitman's poem “A Noiseless Patient Spider” to illustrate the process of interpreting a poem, and explains the relevance of two psychological mechanisms, analogy and conceptual combination, to metaphor. He outlines ideas first sketched by Coleridge—who called poetry “the best words in their best order”—and links them to modern research on the interplay between cognition and emotion, controlled and associative thinking, memory and creativity. Building on Emily Dickinson's declaration “the brain is wider than the sky,” Holyoak suggests that the control and default networks in the brain may combine to support creativity. He also considers, among other things, the interplay of sound and meaning in poetry; symbolism in the work of Yeats, Jung, and others; indirect communication in poems; the mixture of active and passive processes in creativity; and whether artificial intelligence could ever achieve poetic authenticity. Guided by Holyoak, we can begin to trace the outlines of creativity through the mechanisms of metaphor.

The ability to write clearly is critical to any scientific career. The Scientist's Guide to Writing provides practical advice to help scientists become more effective writers so that their ideas have the greatest possible impact.
Drawing on his own experience as a scientist, graduate adviser, and editor, Stephen Heard emphasizes that the goal of all scientific writing should be absolute clarity; that good writing takes deliberate practice; and that what many scientists need are not long lists of prescriptive rules but rather direct engagement with their behaviors and attitudes when they write. He combines advice on such topics as how to generate and maintain writing momentum with practical tips on structuring a scientific paper, revising a first draft, handling citations, responding to peer reviews, managing coauthorships, and more.
In an accessible, informal tone, The Scientist's Guide to Writing explains essential techniques that students, postdoctoral researchers, and early-career scientists need to write more clearly, efficiently, and easily.
Emphasizes writing as a process, not just a product
Encourages habits that improve motivation and productivity
Explains the structure of the scientific paper and the function of each part
Provides detailed guidance on submission, review, revision, and publication
Addresses issues related to coauthorship, English as a second language, and more

Teaching students to become better consumers of psychological research. Keith Stanovich's widely used and highly acclaimed book presents a short introduction to the critical thinking skills that will help students to better understand the subject matter of psychology. How to Think Straight about Psychology, 10e helps students recognize pseudoscience and be able to distinguish it from true psychological research, aiding students to become more discriminating consumers of psychological information. Learning Goals Upon completing this book, readers should be able to: * Evaluate psychological claims they encounter in the general media. * Distinguish between pseudoscience and true psychological research. * Apply psychological knowledge to better understand events in the world around them.

This well-respected text is designed for the first course in probability and statistics taken by students majoring in Engineering and the Computing Sciences. The prerequisite is one year of calculus. The text offers a balanced presentation of applications and theory. The authors take care to develop the theoretical foundations for the statistical methods presented at a level that is accessible to students with only a calculus background. They explore the practical implications of the formal results to problem-solving so that students gain an understanding of the logic behind the techniques as well as practice in using them. The examples, exercises, and applications were chosen specifically for students in engineering and computer science, and include opportunities for real data analysis.

What if the real key to a richer and more fulfilling career was not to create and scale a new start-up, but rather, to be able to work for yourself, determine your own hours, and become a (highly profitable) and sustainable company of one? Suppose the better—and smarter—solution is simply to remain small? This book explains how to do just that.
Company of One is a refreshingly new approach centered on staying small and avoiding growth, for any size business. Not as a freelancer who only gets paid on a per piece basis, and not as an entrepreneurial start-up that wants to scale as soon as possible, but as a small business that is deliberately committed to staying that way. By staying small, one can have freedom to pursue more meaningful pleasures in life, and avoid the headaches that result from dealing with employees, long meetings, or worrying about expansion. Company of One introduces this unique business strategy and explains how to make it work for you, including how to generate cash flow on an ongoing basis.
Paul Jarvis left the corporate world when he realized that working in a high-pressure, high profile world was not his idea of success. Instead, he now works for himself out of his home on a small, lush island off of Vancouver, and lives a much more rewarding and productive life. He no longer has to contend with an environment that constantly demands more productivity, more output, and more growth.
In Company of One, Jarvis explains how you can find the right pathway to do the same, including planning how to set up your shop, determining your desired revenues, dealing with unexpected crises, keeping your key clients happy, and of course, doing all of this on your own.

Automated testing is a cornerstone of agile development. An effective testing strategy will deliver new functionality more aggressively, accelerate user feedback, and improve quality. However, for many developers, creating effective automated tests is a unique and unfamiliar challenge. xUnit Test Patterns is the definitive guide to writing automated tests using xUnit, the most popular unit testing framework in use today. Agile coach and test automation expert Gerard Meszaros describes 68 proven patterns for making tests easier to write, understand, and maintain. He then shows you how to make them more robust and repeatable--and far more cost-effective. Loaded with information, this book feels like three books in one. The first part is a detailed tutorial on test automation that covers everything from test strategy to in-depth test coding. The second part, a catalog of 18 frequently encountered "test smells," provides trouble-shooting guidelines to help you determine the root cause of problems and the most applicable patterns. The third part contains detailed descriptions of each pattern, including refactoring instructions illustrated by extensive code samples in multiple programming languages. Topics covered include * Writing better tests--and writing them faster * The four phases of automated tests: fixture setup, exercising the system under test, result verification, and fixture teardown * Improving test coverage by isolating software from its environment using Test Stubs and Mock Objects * Designing software for greater testability * Using test "smells" (including code smells, behavior smells, and project smells) to spot problems and know when and how to eliminate them * Refactoring tests for greater simplicity, robustness, and execution speed This book will benefit developers, managers, and testers working with any agile or conventional development process, whether doing test-driven development or writing the tests last. While the patterns and smells are especially applicable to all members of the xUnit family, they also apply to next-generation behavior-driven development frameworks such as RSpec and JBehave and to other kinds of test automation tools, including recorded test tools and data-driven test tools such as Fit and FitNesse. Visual Summary of the Pattern Language Foreword Preface Acknowledgments Introduction Refactoring a Test PART I: The Narratives Chapter 1 A Brief Tour Chapter 2 Test Smells Chapter 3 Goals of Test Automation Chapter 4 Philosophy of Test Automation Chapter 5 Principles of Test Automation Chapter 6 Test Automation Strategy Chapter 7 xUnit Basics Chapter 8 Transient Fixture Management Chapter 9 Persistent Fixture Management Chapter 10 Result Verification Chapter 11 Using Test Doubles Chapter 12 Organizing Our Tests Chapter 13 Testing with Databases Chapter 14 A Roadmap to Effective Test Automation PART II: The Test Smells Chapter 15 Code Smells Chapter 16 Behavior Smells Chapter 17 Project Smells PART III: The Patterns Chapter 18 Test Strategy Patterns Chapter 19 xUnit Basics Patterns Chapter 20 Fixture Setup Patterns Chapter 21 Result Verification Patterns Chapter 22 Fixture Teardown Patterns Chapter 23 Test Double Patterns Chapter 24 Test Organization Patterns Chapter 25 Database Patterns Chapter 26 Design-for-Testability Patterns Chapter 27 Value Patterns PART IV: Appendixes Appendix A Test Refactorings Appendix B xUnit Terminology Appendix C xUnit Family Members Appendix D Tools Appendix E Goals and Principles Appendix F Smells, Aliases, and Causes Appendix G Patterns, Aliases, and Variations Glossary References Index

Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into deep learning architectures is crucial for creating systems that can learn, reason, and generalize from this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings, generalizations of convolutional neural networks to graph-structured data, and neural message-passing approaches inspired by belief propagation. These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical synthesis, 3D vision, recommender systems, question answering, and social network analysis.
This book provides a synthesis and overview of graph representation learning. It begins with a discussion of the goals of graph representation learning as well as key methodological foundations in graph theory and network analysis. Following this, the book introduces and reviews methods for learning node embeddings, including random-walk-based methods and applications to knowledge graphs. It then provides a technical synthesis and introduction to the highly successful graph neural network (GNN) formalism, which has become a dominant and fast-growing paradigm for deep learning with graph data. The book concludes with a synthesis of recent advancements in deep generative models for graphs--a nascent but quickly growing subset of graph representation learning.