Optimering

'Lucid, entertaining and precise... a brilliant warning about the gamification of everyday life' Tim Clare, GuardianIs this the game you want to be playing?Scoring systems are everywhere. Underpinning our daily lives – whether it’s the fit bits on our wrists, likes on social media, and even school rankings – they have become pervasive and increasingly dangerous, warping our desires and outsourcing our values to external institutions. Instead of encouraging us to be more playful, to take pleasure in the journey of striving towards a goal, institutions, corporations and bureaucracies weaponize scoring systems to impose their own interests. No matter what, we always seem to be playing by someone else’s rules.In The Score, philosopher C. Thi Nguyen shows us how this newly ‘gamified’ world has fundamentally captured our value systems, turning what might be moral or personal life choices into numerical data, and forcing us to prioritise what can be measured and monetized over what is truly meaningful to us.A life-long lover of online and board games himself, Nguyen argues that we should not stop playing games but rather take a step back and become more aware of their immersive and profound power, so that we might chart a way towards more creative and joyful lives. To start playing our own game.

Game theory means rigorous strategic thinking. It’s the art of anticipating your opponent’s next moves, knowing full well that your rival is trying to do the same thing to you. Though parts of game theory involve simple common sense, much is counterintuitive, and it can only be mastered by developing a new way of seeing the world. Using a diverse array of rich case studies—from pop culture, TV, movies, sports, politics, and history—the authors show how nearly every business and personal interaction has a game-theory component to it. Mastering game theory will make you more successful in business and life, and this lively book is the key to that mastery.

The scientific study of complex systems has transformed a wide range of disciplines in recent years, enabling researchers in both the natural and social sciences to model and predict phenomena as diverse as earthquakes, global warming, demographic patterns, financial crises, and the failure of materials. In this book, Didier Sornette boldly applies his varied experience in these areas to propose a simple, powerful, and general theory of how, why, and when stock markets crash. Most attempts to explain market failures seek to pinpoint triggering mechanisms that occur hours, days, or weeks before the collapse. Sornette proposes a radically different view: the underlying cause can be sought months and even years before the abrupt, catastrophic event in the build-up of cooperative speculation, which often translates into an accelerating rise of the market price, otherwise known as a "bubble." Anchoring his sophisticated, step-by-step analysis in leading-edge physical and statistical modeling techniques, he unearths remarkable insights and some predictions--among them, that the "end of the growth era" will occur around 2050.Sornette probes major historical precedents, from the decades-long "tulip mania" in the Netherlands that wilted suddenly in 1637 to the South Sea Bubble that ended with the first huge market crash in England in 1720, to the Great Crash of October 1929 and Black Monday in 1987, to cite just a few. He concludes that most explanations other than cooperative self-organization fail to account for the subtle bubbles by which the markets lay the groundwork for catastrophe. Any investor or investment professional who seeks a genuine understanding of looming financial disasters should read this book. Physicists, geologists, biologists, economists, and others will welcome Why Stock Markets Crash as a highly original "scientific tale," as Sornette aptly puts it, of the exciting and sometimes fearsome--but no longer quite so unfathomable--world of stock markets.

Optimization is a foundational topic in mathematics, underpinning nearly all of our modern industrial and technological world. Assuming only basic knowledge of linear algebra and calculus, this book provides a rapid, yet thorough, overview of applied mathematical optimization for advanced undergraduates, beginning graduate students, or practitioners in science and engineering. The text opens with an "Optimization Bootcamp", introducing methods at a beginning level, before progressing to deep-dives into advanced topics and research-ready methods. The focus throughout is on modern applications of machine learning, inverse problems, and control. Rich pedagogy includes Python code with simple working examples and advanced case studies. Every section is accompanied by YouTube lectures to encourage interaction with the material. Using intuitive explanations, this book makes the material as simple and interesting as possible, while still having the depth, breadth and precision required to empower use in research and real-world applications.

The million copy international bestseller, critically acclaimed and translated into over 25 languages. As influential today as when it was first published, The Selfish Gene has become a classic exposition of evolutionary thought. Professor Dawkins articulates a gene's eye view of evolution - a view giving centre stage to these persistent units of information, and in which organisms can be seen as vehicles for their replication. This imaginative, powerful, and stylistically brilliant work not only brought the insights of Neo-Darwinism to a wide audience, but galvanized the biology community, generating much debate and stimulating whole new areas of research. Forty years later, its insights remain as relevant today as on the day it was published. This 40th anniversary edition includes a new epilogue from the author discussing the continuing relevance of these ideas in evolutionary biology today, as well as the original prefaces and foreword, and extracts from early reviews. Oxford Landmark Science books are 'must-read' classics of modern science writing which have crystallized big ideas, and shaped the way we think.

Elementär optimeringslära är ett grundläggande komplement till avancerade böcker inom optimeringslära. I boken läggs stor vikt vid att i lagom takt introducera läsaren till den teori och de tekniker som behövs inom grundläggande optimeringslära. Boken innehåller över 200 lösta exempel och mer än 400 övningsuppgifter med svar.Elementär optimeringslära inleds med en repetition av grundläggande matematikkunskaper om algebra, ekvationer, matriser, funktioner och derivata. Därefter behandlas linjär optimering, först i två variabler med fokus på geometrisk förståelse och därefter, i det allmänna fallet, med simplexmetoden. Denna metod tillämpas i boken även inom det spännande matematikområdet spelteori. Boken redogör för olika metoder för optimering av allmänna tvåvariabelfunktioner, dels över kompakta områden, dels med Lagranges sats givet ett bivillkor och dels med Hessianen. Boken tar avslutningsvis upp optimering på grafer med Kruskals, Prims och Dijkstras algoritmer.Boken vänder sig till studerande inom naturvetenskap, teknik eller ekonomi vid högskola och universitet. Boken kan också med fördel användas som en källa till fördjupning inom gymnasiets senare matematikkurser.

Det här är den andra boken i serien tipsboken. Den första boken utföll ett statistiksystem på 81 rader gällande topptipset med alla rätt den 5 januari i år och en utdelning på 73 809 kronor. Här i boken finns nya statistiksystem som du bara skriver av och lämnar in. Spelstrategi för matchen. System för oddset powerplay, tipset 1 x 2, V75, bomben, samt oddset.Resultat & utdelningar, samt statistik.Boken riktar sig till dig som vill vinna oftare och mer än vad du kanske gör idag.

'Wooldridge is like the teacher you wish you'd had'GUARDIAN'This book is simply brilliant . . . I learned so much'SIR DAVID SPIEGELHALTER, UNIVERSITY OF CAMBRIDGE'Fresh, clever and playful'MATT RIDLEY, AUTHOR OF THE ORIGINS OF VIRTUE'Michael explains the complex, strategic structures of our world with masterful beauty'MILIND TAMBE, HARVARD UNIVERSITY'Effortlessly covers a broad swath of core ideas in game theory, with a sprinkle of British humour'EDITH ELKIND, NORTHWESTERN UNIVERSITY'A wonderful book'YOAV SHOHAM, STANFORD UNIVERSITY______A fascinating deep-dive into game theory, its history and its practical applications by award-winning expert on computer science and artificial intelligence.Most of us have some idea about game theory. Concepts like zero-sum games and the prisoner's dilemma crop up in films, novels and casual conversation, often as shorthand for cut-throat competition or inevitable betrayal. But game theory, the science behind these ideas, is widely misunderstood. All too often it's seen solely as the science of conflict and greed. In fact, this field has a lot to teach us about how to make a better world. It shows us just what it takes to enable cooperation and mutual benefit.This essential primer presents twenty one 'life lessons from game theory', which illustrate the key ideas in the field, and which are packed with real world examples: from overfishing in the Atlantic; to the Cuban Missile Crisis; to security measures at international airports; to advertising wars between major brands. This is a hopeful and practical book that highlights the value of game theory and provides a course correction for its integration into the real world.

The principles of game theory apply to a wide range of topics in biology. This book presents the central concepts in evolutionary game theory and provides an authoritative and up-to-date account. The focus is on concepts that are important for biologists in their attempts to explain observations. This strong connection between concepts and applications is a recurrent theme throughout the book which incorporates recent and traditional ideas from animal psychology, neuroscience, and machine learning that provide a mechanistic basis for behaviours shown by players of a game. The approaches taken to modelling games often rest on idealized and unrealistic assumptions whose limitations and consequences are not always appreciated. The authors provide a novel reassessment of the field, highlighting how to overcome limitations and identifying future directions.Game Theory in Biology is an advanced textbook suitable for graduate level students as well as professional researchers (both empiricists and theoreticians) in the fields of behavioural ecology and evolutionary biology. It will also be of relevance to a broader interdisciplinary audience including psychologists and neuroscientists.

'Wooldridge is like the teacher you wish you'd had' GUARDIAN'This book is simply brilliant . . . I learned so much' SIR DAVID SPIEGELHALTER, UNIVERSITY OF CAMBRIDGE'Fresh, clever and playful' MATT RIDLEY, AUTHOR OF THE ORIGINS OF VIRTUE'Michael explains the complex, strategic structures of our world with masterful beauty'MILIND TAMBE, HARVARD UNIVERSITY'Effortlessly covers a broad swath of core ideas in game theory, with a sprinkle of British humour'EDITH ELKIND, NORTHWESTERN UNIVERSITY'A wonderful book' YOAV SHOHAM, STANFORD UNIVERSITY______A fascinating deep-dive into game theory, its history and its practical applications by award-winning expert on computer science and artificial intelligence.Most of us have some idea about game theory. Concepts like zero-sum games and the prisoner's dilemma crop up in films, novels and casual conversation, often as shorthand for cut-throat competition or inevitable betrayal. But game theory, the science behind these ideas, is widely misunderstood. All too often it's seen solely as the science of conflict and greed. In fact, this field has a lot to teach us about how to make a better world. It shows us just what it takes to enable cooperation and mutual benefit.This essential primer presents twenty one 'life lessons from game theory', which illustrate the key ideas in the field, and which are packed with real world examples: from overfishing in the Atlantic; to the Cuban Missile Crisis; to security measures at international airports; to advertising wars between major brands. This is a hopeful and practical book that highlights the value of game theory and provides a course correction for its integration into the real world.

This practical guide to optimization combines mathematical theory with hands-on coding examples to explore how Python can be used to model problems and obtain the best possible solutions. Presenting a balance of theory and practical applications, it is the ideal resource for upper-undergraduate and graduate students in applied mathematics, data science, business, industrial engineering and operations research, as well as practitioners in related fields. Beginning with an introduction to the concept of optimization, this text presents the key ingredients of an optimization problem and the choices one needs to make when modeling a real-life problem mathematically. Topics covered range from linear and network optimization to convex optimization and optimizations under uncertainty. The book's Python code snippets, alongside more than 50 Jupyter notebooks on the author's GitHub, allow students to put the theory into practice and solve problems inspired by real-life challenges, while numerous exercises sharpen students' understanding of the methods discussed.

We all played tag when we were kids. What most of us don't realize is that this simple chase game is in fact an application of pursuit theory, and that the same principles of games like tag, dodgeball, and hide-and-seek are also at play in military strategy, high-seas chases by the Coast Guard, and even romantic pursuits. In Chases and Escapes, Paul Nahin gives us the first complete history of this fascinating area of mathematics, from its classical analytical beginnings to the present day. Drawing on game theory, geometry, linear algebra, target-tracking algorithms, and much more, Nahin also offers an array of challenging puzzles with their historical background and broader applications. Chases and Escapes includes solutions to all problems and provides computer programs that readers can use for their own cutting-edge analysis. Now with a gripping new preface on how the Enola Gay escaped the shock wave from the atomic bomb dropped on Hiroshima, this book will appeal to anyone interested in the mathematics that underlie pursuit and evasion.

'BRILLIANTLY CLEAR AND CAPTIVATING PROSE' STEPHEN FRY A WATERSTONES BOOK OF YEAR 2023 An award-winning mathematician explores the maths behind the games we love and why we love to play them. Where should you move first in Connect 4? Which property is best in Monopoly? How can pi help you win Rock Paper Scissors? Crossing oceans, continents and millennia, award-winning mathematician Marcus du Sautoy explores how maths and games have always been deeply intertwined. As well as being integral to human psychology and culture throughout the ages, games provided the first opportunities for deep mathematical insight into the world. This grand adventure teaches us how to strategise, play better and win more often.‘The subject matter is fun (I mean, isn’t it quite literally the definition of fun?) and du Sautoy’s enthusiasm is infectious’ THE SUNDAY TIMES‘Lively, creative and humane – exactly as one would expect from Marcus du Sautoy’ TIM HARFORD, author of How To Make The World Add Up'A delightful and addictive celebration of games. You’ll keep wanting one more go' DARA Ó BRIAIN, author of Is There Anybody Out There?‘You do not need to be a seasoned player nor a skilled mathematician to relish this enchanting read. However, this book may just encourage you to become one or the other’ REINER KNIZIA, award-winning game designer

This book is the first comprehensive guide to logic-based Benders decomposition (LBBD), a general and versatile method for breaking large, complex optimization problems into components that are small enough for practical solution.  The author introduces logic-based Benders decomposition for optimization, which substantially generalizes the classical Benders method.  It can reduce solution times by orders of magnitude and allows decomposition to be applied to a much wider variety of optimization problems.  On the theoretical side, this book provides a full account of inference duality concepts that underlie LBBD, as well as a description of how LBBD can be combined with stochastic and robust optimization, heuristic methods, and decision diagrams.  It also clarifies the connection between LBBD and combinatorial Benders cuts for mixed integer programming.  On the practical side, it explains how LBBD has been applied to a rapidly growingvariety of problem domains.  After describing basic theory, this book provides a comprehensive review of the rapidly growing literature that describes these applications, in each case explaining how LBBD is adapted to the problem at hand.  In doing so this work provides a sourcebook of ideas for applying LBBD to new problems as they arise.

This comprehensive textbook introduces readers to the principal ideas and applications of game theory, in a style that combines rigor with accessibility. Steven Tadelis begins with a concise description of rational decision making, and goes on to discuss strategic and extensive form games with complete information, Bayesian games, and extensive form games with imperfect information. He covers a host of topics, including multistage and repeated games, bargaining theory, auctions, rent-seeking games, mechanism design, signaling games, reputation building, and information transmission games. Unlike other books on game theory, this one begins with the idea of rationality and explores its implications for multiperson decision problems through concepts like dominated strategies and rationalizability. Only then does it present the subject of Nash equilibrium and its derivatives. Game Theory is the ideal textbook for advanced undergraduate and beginning graduate students. Throughout, concepts and methods are explained using real-world examples backed by precise analytic material.The book features many important applications to economics and political science, as well as numerous exercises that focus on how to formalize informal situations and then analyze them. * Introduces the core ideas and applications of game theory * Covers static and dynamic games, with complete and incomplete information * Features a variety of examples, applications, and exercises * Topics include repeated games, bargaining, auctions, signaling, reputation, and information transmission * Ideal for advanced undergraduate and beginning graduate students * Complete solutions available to teachers and selected solutions available to students

Revised with second printing, 2018.Optimization, or mathematical programming, is a fundamental subject within decision science and operations research in which mathematical decision models are constructed, analyzed, and solved.Andreasson provides a basis for the analysis of optimization models and candidate optimal solutions for continuous optimization models. Elementary but rigorous mathematics and linear algebra underlie the workings of convexity and duality, and necessary/sufficient local/global optimality conditions for continuous optimization problems. Natural algorithms are developed from these optimality conditions, and their most important convergence characteristics are analyzed. The author answers many more “Why?” and “Why not?” than “How?” questions.The author provides lecture, exercise and reading material for a first course on continuous optimization and mathematical programming. It is geared towards third-year students, and has already been used for nearly ten years. The preface describes the main changes to the first edition.The book can be used in mathematical optimization courses at engineering, economics, and business schools. It is a perfect starting point for anyone who wishes to develop an understanding of the subject before actually applying it.

Optimists believe this is the best of all possible worlds. And pessimists fear that might really be the case. But what is the best of all possible worlds? How do we define it? This question has preoccupied philosophers and theologians for ages, but there was a time, during the seventeenth and eighteenth centuries, when scientists and mathematicians felt they could provide the answer. This book is their story. Ivar Ekeland here takes the reader on a journey through scientific attempts to envision the best of all possible worlds. He begins with the French physicist Maupertuis, whose least action principle, Ekeland shows, was a pivotal breakthrough in mathematics, because it was the first expression of the concept of optimization, or the creation of systems that are the most efficient or functional. Tracing the profound impact of optimization and the unexpected ways in which it has influenced the study of mathematics, biology, economics, and even politics, Ekeland reveals how the idea has driven some of our greatest intellectual breakthroughs. The result is a dazzling display of erudition - one that will be essential reading for popular-science buffs and historians of science alike.

A Beautiful Mind is Sylvia Nasar's award-winning biography about the mystery of the human mind, the triumph over incredible adversity, and the healing power of love.At the age of thirty-one, John Nash, mathematical genius, suffered a devastating breakdown and was diagnosed with schizophrenia. Yet after decades of leading a ghost-like existence, he was to re-emerge to win a Nobel Prize and world acclaim. A Beautiful Mind has inspired the Oscar-winning film directed by Ron Howard and featuring Russell Crowe in the lead role of John Nash.

This book is intended as a textbook for a first course in the theory of functions of one complex variable for students who are mathematically mature enough to understand and execute E - 8 arguments. The actual pre­ requisites for reading this book are quite minimal; not much more than a stiff course in basic calculus and a few facts about partial derivatives. The topics from advanced calculus that are used (e.g., Leibniz's rule for differ­ entiating under the integral sign) are proved in detail. Complex Variables is a subject which has something for all mathematicians. In addition to having applications to other parts of analysis, it can rightly claim to be an ancestor of many areas of mathematics (e.g., homotopy theory, manifolds). This view of Complex Analysis as "An Introduction to Mathe­ matics" has influenced the writing and selection of subject matter for this book. The other guiding principle followed is that all definitions, theorems, etc.

This is the classic work upon which modern-day game theory is based. What began more than sixty years ago as a modest proposal that a mathematician and an economist write a short paper together blossomed, in 1944, when Princeton University Press published Theory of Games and Economic Behavior. In it, John von Neumann and Oskar Morgenstern conceived a groundbreaking mathematical theory of economic and social organization, based on a theory of games of strategy. Not only would this revolutionize economics, but the entirely new field of scientific inquiry it yielded--game theory--has since been widely used to analyze a host of real-world phenomena from arms races to optimal policy choices of presidential candidates, from vaccination policy to major league baseball salary negotiations. And it is today established throughout both the social sciences and a wide range of other sciences.This sixtieth anniversary edition includes not only the original text but also an introduction by Harold Kuhn, an afterword by Ariel Rubinstein, and reviews and articles on the book that appeared at the time of its original publication in the New York Times, tthe American Economic Review, and a variety of other publications. Together, these writings provide readers a matchless opportunity to more fully appreciate a work whose influence will yet resound for generations to come.

A decision procedure is an algorithm that, given a decision problem, terminates with a correct yes/no answer. Here, the authors focus on theories that are expressive enough to model real problems, but are still decidable. Specifically, the book concentrates on decision procedures for first-order theories that are commonly used in automated verification and reasoning, theorem-proving, compiler optimization and operations research. The techniques described in the book draw from fields such as graph theory and logic, and are routinely used in industry.The authors introduce the basic terminology of SAT, Satisfiability Modulo Theories (SMT) and the DPLL(T) framework. Then, in separate chapters, they study decision procedures for propositional logic; equalities and uninterpreted functions; linear arithmetic; bit vectors; arrays; pointer logic; and quantified formulas. They also study the problem of deciding combined theories based on the Nelson-Oppen procedure.Thefirst edition of this book was adopted as a textbook in courses worldwide. It was published in 2008 and the field now called SMT was then in its infancy, without the standard terminology and canonic algorithms it has now; this second edition reflects these changes. It brings forward the DPLL(T) framework. It also expands the SAT chapter with modern SAT heuristics, and includes a new section about incremental satisfiability, and the related Constraints Satisfaction Problem (CSP).  The chapter about quantifiers was expanded with a new section about general quantification using E-matching and a section about Effectively Propositional Reasoning (EPR). The book also includes a new chapter on the application of SMT in industrial software engineering and in computational biology, coauthored by Nikolaj Bjørner and Leonardo de Moura, and Hillel Kugler, respectively.Each chapter includes a detailed bibliography and exercises. Lecturers’ slides and a C++ library for rapid prototyping of decision procedures are available from the authors’ website.

Dynamic programming (DP) is a sub-field of optimization concerned with sequential decision making over time. The essential ideas of DP have been adopted in many applications, from robotics and AI to the sequencing of DNA. It is used around the world to control aircraft, route shipping, test products, recommend information on media platforms and solve major research problems. Dynamic Programming: Finite States treats the theory of dynamic programming and its applications in economics, finance, and operations research. It contains classical results on dynamic programming as well as extensions created by researchers and practitioners as they wrestle with formulating and solving dynamic models that can explain patterns observed in data. Adopting an abstract framework that provides great generality, this book facilitates rapid progress to the research frontier by combining rigorous theory with numerous applications, many solved exercises, and detailed open-source computer code.

​This book both summarizes the basic theory of evolutionary games and explains their developing applications, giving special attention to the 2-player, 2-strategy game. This game, usually termed a "2×2 game” in the jargon, has been deemed most important because it makes it possible to posit an archetype framework that can be extended to various applications for engineering, the social sciences, and even pure science fields spanning theoretical biology, physics, economics, politics, and information science. The 2×2 game is in fact one of the hottest issues in the field of statistical physics. The book first shows how the fundamental theory of the 2×2 game, based on so-called replicator dynamics, highlights its potential relation with nonlinear dynamical systems. This analytical approach implies that there is a gap between theoretical and reality-based prognoses observed in social systems of humans as well as in those of animal species. The book explains that this perceived gap is theresult of an underlying reciprocity mechanism called social viscosity. As a second major point, the book puts a sharp focus on network reciprocity, one of the five fundamental mechanisms for adding social viscosity to a system and one that has been a great concern for study by statistical physicists in the past decade. The book explains how network reciprocity works for emerging cooperation, and readers can clearly understand the existence of substantial mechanics when the term "network reciprocity" is used. In the latter part of the book, readers will find several interesting examples in which evolutionary game theory is applied. One such example is traffic flow analysis. Traffic flow is one of the subjects that fluid dynamics can deal with, although flowing objects do not comprise a pure fluid but, rather, are a set of many particles. Applying the framework of evolutionary games to realistic traffic flows, the book reveals that social dilemma structures lie behind traffic flow.

Evolutionary game theory originated in population biology from the realisation that frequency-dependent fitness introduced a strategic element into evolution. Since its development, evolutionary game theory has been adopted by many social scientists, and philosophers, to analyse interdependent decision problems played by boundedly rational individuals. Its study has led to theoretical innovations of great interest for the biological and social sciences. For example, theorists have developed a number of dynamical models which can be used to study how populations of interacting individuals change their behaviours over time. In this introduction, this Element covers the two main approaches to evolutionary game theory: the static analysis of evolutionary stability concepts, and the study of dynamical models, their convergence behaviour and rest points. This Element also explores the many fascinating, and complex, connections between the two approaches.

Optimering är en komplett grundbok i optimeringslära som passar för både enklare och mer avancerade kurser på universitetsnivå.

Läsaren får en mångsidig verktygslåda för att lösa praktiska optimeringsproblem. Fokus ligger på användbara metoder snarare än teori.

Andra utmärkande drag:

Täcker alla delar av optimeringens grunder Är ovanligt grundlig i behandlingen av kombinatorisk optimering och optimering av grafer Innehåller en stor mängd övningsuppgifter, tillräckligt för både lärarledda lektioner och hemuppgifter

Språket är enkelt och beskrivningarna inleds genomgående med exempel där författaren konkret förklarar när och hur metoderna kan användas.

Om författarnaFörfattaren Kaj Holmberg är professor i optimeringslära vid Linköpings universitet och aktiv forskare. Han har undervisat i ämnet i över 30 år och nominerats till Linköpings teknologers studentkårs pris för bästa pedagog.

We make choices all the time - about trivial matters, about how to spend our money, about how to spend our time, about what to do with our lives. And we are also constantly judging the decisions other people make as rational or irrational. But what kind of criteria are we applying when we say that a choice is rational? What guides our own choices, especially in cases where we don't have complete information about the outcomes? What strategies should be applied in making decisions which affect a lot of people, as in the case of government policy?This book explores what it means to be rational in all these contexts. It introduces ideas from economics, philosophy, and other areas, showing how the theory applies to decisions in everyday life, and to particular situations such as gambling and the allocation of resources.ABOUT THE SERIES: The Very Short Introductions series from Oxford University Press contains hundreds of titles in almost every subject area. These pocket-sized books are the perfect way to get ahead in a new subject quickly. Our expert authors combine facts, analysis, perspective, new ideas, and enthusiasm to make interesting and challenging topics highly readable.