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The Art of the Infinite: Our Lost Language of Numbers
by Robert Kaplan Ellen KaplanIt is easy to be wary of mathematics - but as this book shows, drawing on science, literature and philosophy, its patterns are evrywhere. In witty and eloquent prose, Robert and Ellen Kaplan take mathematics back to its estranged audience, bringing understanding and clarity to a traditionally difficult subject, and revealing the beauty behind the equations. Only by letting loose our curiosity can we learn to appreciate the wonder that can be found in mathematics - an 'art' invented by humans, which is also timeless.
The Art of the Infinite: The Pleasures of Mathematics
by Robert Kaplan Ellen KaplanA witty, conversational, and accessible tour of math's profoundest mysteries.Mathematical symbols, for mathematicians, store worlds of meaning, leap continents and centuries. But we need not master symbols to grasp the magnificent abstractions they represent, and to which all art aspires. Through language, anyone can come to delight in the works of mathematical art, which are among our kind's greatest glories.Taking the concept of infinity, in its countless guises, as a starting point and a helpful touchstone, the founders of Harvard's pioneering Math Circle program Robert and Ellen Kaplan guide us through the “Republic of Numbers,” where we meet both its upstanding citizens and its more shadowy dwellers, explore realms where only the imagination can go, and grapple with math's most profound uncertainties, including the question of truth itself-do we discover mathematical principles, or invent them?
The Art of the Intelligible: An Elementary Survey of Mathematics in its Conceptual Development (The Western Ontario Series in Philosophy of Science #63)
by J. BellA compact survey, at the elementary level, of some of the most important concepts of mathematics. Attention is paid to their technical features, historical development and broader philosophical significance. Each of the various branches of mathematics is discussed separately, but their interdependence is emphasised throughout. Certain topics - such as Greek mathematics, abstract algebra, set theory, geometry and the philosophy of mathematics - are discussed in detail. Appendices outline from scratch the proofs of two of the most celebrated limitative results of mathematics: the insolubility of the problem of doubling the cube and trisecting an arbitrary angle, and the Gödel incompleteness theorems. Additional appendices contain brief accounts of smooth infinitesimal analysis - a new approach to the use of infinitesimals in the calculus - and of the philosophical thought of the great 20th century mathematician Hermann Weyl. Readership: Students and teachers of mathematics, science and philosophy. The greater part of the book can be read and enjoyed by anyone possessing a good high school mathematics background.
The Art of Theoretical Biology
This beautifully crafted book collects images, which were created during the process of research in all fields of theoretical biology. Data analysis, numerical treatment of a model, or simulation results yield stunning images, which represent pieces of art just by themselves. The approach of the book is to present for each piece of visualization a lucid synopsis of the scientific background as well as an outline of the artistic vision.
The Art of Uncertainty: How to Navigate Chance, Ignorance, Risk and Luck
by David Spiegelhalter‘Probably the UK’s greatest living statistician’ TelegraphFrom the UK’s ‘statistical national treasure’, a clever and data-driven guide to how we can live with risk and uncertaintyWe live in a world where uncertainty is inevitable. How should we deal with what we don’t know? And what role do chance, luck and coincidence play in our lives?David Spiegelhalter has spent his career dissecting data in order to understand risks and assess the chances of what might happen in the future. In The Art of Uncertainty, he gives readers a window onto how we can all do this better.In engaging, crystal-clear prose, he takes us through the principles of probability, showing how it can help us think more analytically about everything from medical advice to pandemics and climate change forecasts, and explores how we can update our beliefs about the future in the face of constantly changing experience. Along the way, he explains why roughly 40% of football results come down to luck rather than talent, how the National Risk Register assesses near-term risks to the United Kingdom, and why we can be so confident that two properly shuffled packs of cards have never, ever been in the exact same order.Drawing on a wide range of captivating real-world examples, this is an essential guide to navigating uncertainty while also having the humility to admit what we do not know
The Art Of Writing Efficient Programs: An Advanced Programmers Guide To Efficient Hardware Utilization And Compiler Optimizations Using C++ Examples
by Fedor G. PikusAn advanced programmer's guide to efficient hardware utilization and compiler optimizations using C++ examples
Arthur's Invariant Trace Formula and Comparison of Inner Forms
by Yuval Z. FlickerThis monograph provides an accessible and comprehensive introduction to James Arthur’s invariant trace formula, a crucial tool in the theory of automorphic representations. It synthesizes two decades of Arthur’s research and writing into one volume, treating a highly detailed and often difficult subject in a clearer and more uniform manner without sacrificing any technical details. The book begins with a brief overview of Arthur’s work and a proof of the correspondence between GL(n) and its inner forms in general. Subsequent chapters develop the invariant trace formula in a form fit for applications, starting with Arthur’s proof of the basic, non-invariant trace formula, followed by a study of the non-invariance of the terms in the basic trace formula, and, finally, an in-depth look at the development of the invariant formula. The final chapter illustrates the use of the formula by comparing it for G’ = GL(n) and its inner form GArthur’s Invariant Trace Formula and Comparison of Inner Forms will appeal to advanced graduate students, researchers, and others interested in automorphic forms and trace formulae. Additionally, it can be used as a supplemental text in graduate courses on representation theory.
Artifacts in Behavioral Research: Robert Rosenthal and Ralph L. Rosnow's Classic Books
by Robert Rosenthal Ralph L. RosnowThis new combination volume of three-books-in-one, dealing with the topic of artifacts in behavioral research, was designed as both introduction and reminder. It was designed as an introduction to the topic for graduate students, advanced undergraduates, and younger researchers. It was designed as a reminder to more experienced researchers, in and out of academia, that the problems of artifacts in behavioral research, that they may have learned about as beginning researchers, have not gone away. For example, problems of experimenter effects have not been solved. Experimenters still differ in the ways in which they see, interpret, and manipulate their data. Experimenters still obtain different responses from research participants (human or infrahuman) as a function of experimenters' states and traits of biosocial, psychosocial, and situational origins. Experimenters' expectations still serve too often as self-fulfilling prophecies, a problem that biomedical researchers have acknowledged and guarded against better than have behavioral researchers; e.g., many biomedical studies would be considered of unpublishable quality had their experimenters not been blind to experimental condition. Problems of participant or subject effects have also not been solved. We usually still draw our research samples from a population of volunteers that differ along many dimensions from those not finding their way into our research. Research participants are still often suspicious of experimenters' intent, try to figure out what experimenters are after, and are concerned about what the experimenter thinks of them.
Artifacts in Behavioral Research: Robert Rosenthal and Ralph L. Rosnow's Classic Books
by Robert Rosenthal Ralph L. RosnowThis new combination volume of three-books-in-one, dealing with the topic of artifacts in behavioral research, was designed as both introduction and reminder. It was designed as an introduction to the topic for graduate students, advanced undergraduates, and younger researchers. It was designed as a reminder to more experienced researchers, in and out of academia, that the problems of artifacts in behavioral research, that they may have learned about as beginning researchers, have not gone away. For example, problems of experimenter effects have not been solved. Experimenters still differ in the ways in which they see, interpret, and manipulate their data. Experimenters still obtain different responses from research participants (human or infrahuman) as a function of experimenters' states and traits of biosocial, psychosocial, and situational origins. Experimenters' expectations still serve too often as self-fulfilling prophecies, a problem that biomedical researchers have acknowledged and guarded against better than have behavioral researchers; e.g., many biomedical studies would be considered of unpublishable quality had their experimenters not been blind to experimental condition. Problems of participant or subject effects have also not been solved. We usually still draw our research samples from a population of volunteers that differ along many dimensions from those not finding their way into our research. Research participants are still often suspicious of experimenters' intent, try to figure out what experimenters are after, and are concerned about what the experimenter thinks of them.
Artificial Adaptive Systems Using Auto Contractive Maps: Theory, Applications and Extensions (Studies in Systems, Decision and Control #131)
by Paolo Massimo Buscema Giulia Massini Marco Breda Weldon A. Lodwick Francis Newman Masoud Asadi-ZeydabadiThis book offers an introduction to artificial adaptive systems and a general model of the relationships between the data and algorithms used to analyze them. It subsequently describes artificial neural networks as a subclass of artificial adaptive systems, and reports on the backpropagation algorithm, while also identifying an important connection between supervised and unsupervised artificial neural networks. The book’s primary focus is on the auto contractive map, an unsupervised artificial neural network employing a fixed point method versus traditional energy minimization. This is a powerful tool for understanding, associating and transforming data, as demonstrated in the numerous examples presented here. A supervised version of the auto contracting map is also introduced as an outstanding method for recognizing digits and defects. In closing, the book walks the readers through the theory and examples of how the auto contracting map can be used in conjunction with another artificial neural network, the “spin-net,” as a dynamic form of auto-associative memory.
Artificial Boundary Method
by Houde Han Xiaonan Wu"Artificial Boundary Method" systematically introduces the artificial boundary method for the numerical solutions of partial differential equations in unbounded domains. Detailed discussions treat different types of problems, including Laplace, Helmholtz, heat, Schrödinger, and Navier and Stokes equations. Both numerical methods and error analysis are discussed. The book is intended for researchers working in the fields of computational mathematics and mechanical engineering.Prof. Houde Han works at Tsinghua University, China; Prof. Xiaonan Wu works at Hong Kong Baptist University, China.
Artificial Economics and Self Organization: Agent-Based Approaches to Economics and Social Systems (Lecture Notes in Economics and Mathematical Systems #669)
by Stephan Leitner Friederike WallThis volume presents recent advances in the dynamic field of Artificial Economics and its various applications. Artificial Economics provides a structured approach to model and investigate economic and social systems. In particular, this approach is based on the use of agent-based simulations and further computational techniques. The main aim is to analyze the outcomes at the overall systems’ level as results from the agents’ behavior at the micro-level. These emergent characteristics of complex economic and social systems can neither be foreseen nor are they intended. The emergence rather makes these systems function. Artificial Economics especially facilitates the investigation of this emergent systems’ behavior.
Artificial Evolution: 15th International Conference, Évolution Artificielle, EA 2022, Exeter, UK, October 31 – November 2, 2022, Revised Selected Papers (Lecture Notes in Computer Science #14091)
by Pierrick Legrand Arnaud Liefooghe Edward Keedwell Julien Lepagnot Lhassane Idoumghar Nicolas Monmarché Evelyne LuttonThis book constitutes the refereed post-conference proceedings of the 15th International Conference, Évolution Artificielle, EA 2022, held in Exeter, UK, during October 31–November 2, 2022.The 15 full papers were carefully reviewed and selected from 18 submissions. The papers cover a wide range of topics in the field of artificial evolution, including, but not limited to: evolutionary computation, evolutionary optimization, coevolution, artificial life, population dynamics, theory, algorithmic and modeling, implementations.
Artificial General Intelligence: 5th International Conference, AGI 2012, Oxford, UK, December 8-11, 2012. Proceedings (Lecture Notes in Computer Science #7716)
by Joscha Bach Ben Goertzel Matthew IkléThis book constitutes the refereed proceedings of the 5th International Conference on Artificial General Intelligence, AGI 2012, held in Oxford, UK, in December 2012. The 34 revised full papers presented together with 4 invited keynote lectures were carefully reviewed and selected from 80 submissions. The papers are written by leading scientists involved in research and development of AI systems possessing general intelligence at the human level and beyond; with a special focus on humanoid robotics and AGI, cognitive robotics, creativity and AGI, the future evolution of advanced AGIs, and the dynamics of AGI goal systems.
Artificial General Intelligence: 8th International Conference, AGI 2015, AGI 2015, Berlin, Germany, July 22-25, 2015, Proceedings (Lecture Notes in Computer Science #9205)
by Jordi Bieger Ben Goertzel Alexey PotapovThis book constitutes the refereed proceedings of the 8th International Conference on Artificial General Intelligence, AGI 2015, held in Berlin, Germany in July 2015. The 41 papers were carefully reviewed and selected from 72 submissions. The AGI conference series has played and continues to play, a significant role in this resurgence of research on artificial intelligence in the deeper, original sense of the term of “artificial intelligence”. The conferences encourage interdisciplinary research based on different understandings of intelligence and exploring different approaches. AGI research differs from the ordinary AI research by stressing on the versatility and wholeness of intelligence and by carrying out the engineering practice according to an outline of a system comparable to the human mind in a certain sense.
Artificial General Intelligence: 7th International Conference, AGI 2014, Quebec City, QC, Canada, August 1-4, 2014, Proceedings (Lecture Notes in Computer Science #8598)
by Ben Goertzel Laurent Orseau Javier SnaiderThis book constitutes the refereed proceedings of the 7th International Conference on Artificial General Intelligence, AGI 2014, held in Quebec City, QC, Canada, in August 2014. The 22 papers and 8 posters were carefully reviewed and selected from 65 submissions. Researchers have recognized the necessity of returning to the original goals of the field by treating intelligence as a whole. Increasingly, there is a call for a transition back to confronting the more difficult issues of "human-level intelligence" and more broadly artificial general intelligence. AGI research differs from the ordinary AI research by stressing on the versatility and wholeness of intelligence and by carrying out the engineering practice according to an outline of a system comparable to the human mind in a certain sense. The AGI conference series has played and continues to play, a significant role in this resurgence of research on artificial intelligence in the deeper, original sense of the term of "artificial intelligence". The conferences encourage interdisciplinary research based on different understandings of intelligence and exploring different approaches.
Artificial General Intelligence: 14th International Conference, AGI 2021, Palo Alto, CA, USA, October 15–18, 2021, Proceedings (Lecture Notes in Computer Science #13154)
by Ben Goertzel Alexey Potapov Matthew IkléThis book constitutes the refereed proceedings of the 14th International Conference on Artificial General Intelligence, AGI 2021, held as a hybrid event in San Francisco, CA, USA, in October 2021.The 36 full papers presented in this book were carefully reviewed and selected from 50 submissions. The papers cover topics from foundations of AGI, to AGI approaches and AGI ethics, to the roles of systems biology, goal generation, and learning systems, and so much more.
Artificial General Intelligence: 6th International Conference, AGI 2013, Beijing, China, July 31 -- August 3, 2013, Proceedings (Lecture Notes in Computer Science #7999)
by Kai-Uwe Kühnberger Sebastian Rudolph Pei WangThis book constitutes the refereed proceedings of the 6th International Conference on Artificial General Intelligence, AGI 2013, held in Beijing, China, in July/August 2013. The 23 papers (17 full papers, 3 technical communications, and 3 special session papers) were carefully reviewed and selected from various submissions. The volume collects the current research endeavors devoted to develop formalisms, algorithms, and models, as well as systems that are targeted at general intelligence. Similar to the predecessor AGI conferences, researchers proposed different methodologies and techniques in order to bridge the gap between forms of specialized intelligence and general intelligence.
Artificial General Intelligence: 4th International Conference, AGI 2011, Mountain View, CA, USA, August 3-6, 2011, Proceedings (Lecture Notes in Computer Science #6830)
by Jürgen Schmidhuber Kristinn R. Thorisson Moshe LooksThis book constitutes the refereed proceedings of the 4th International Conference on Artificial General Intelligence, AGI 2011, held in Mountain View, CA, USA, in August 2011. The 28 revised full papers and 26 short papers were carefully reviewed and selected from 103 submissions. The papers are written by leading academic and industry researchers involved in scientific and engineering work and focus on the creation of AI systems possessing general intelligence at the human level and beyond.
Artificial Intelligence: 18th International Conference, AIMSA 2018, Varna, Bulgaria, September 12–14, 2018, Proceedings (Lecture Notes in Computer Science #11089)
by Gennady Agre Josef Van Genabith Thierry DeclerckThis book constitutes the refereed proceedings of the 18th International Conference on Artificial Intelligence: Methodology, Systems, and Applications, AIMSA 2018, held in Varna, Bulgaria, in September 2018.The 22 revised full papers and 7 poster papers presented were carefully reviewed and selected from 72 submissions. They cover a wide range of topics in AI: from machine learning to natural language systems, from information extraction to text mining, from knowledge representation to soft computing; from theoretical issues to real-world applications.
Artificial Intelligence: An Introduction to the Big Ideas and their Development (Chapman & Hall/CRC Mathematics and Artificial Intelligence Series)
by Robert H. Chen Chelsea ChenArtificial Intelligence: An Introduction to Big Ideas and their Development, Second Edition guides readers through the history and development of artificial intelligence (AI), from its early mathematical beginnings through to the exciting possibilities of its potential future applications. To make this journey as accessible as possible, the authors build their narrative around accounts of some of the more popular and well-known demonstrations of artificial intelligence, including Deep Blue, AlphaGo and even Texas Hold’em, followed by their historical background, so that AI can be seen as a natural development of the mathematics and computer science of AI. As the book proceeds, more technical descriptions are presented at a pace that should be suitable for all levels of readers, gradually building a broad and reasonably deep understanding and appreciation for the basic mathematics, physics, and computer science that is rapidly developing artificial intelligence as it is today. Features Only mathematical prerequisite is an elementary knowledge of calculus. Accessible to anyone with an interest in AI and its mathematics and computer science. Suitable as a supplementary reading for a course in AI or the History of Mathematics and Computer Science in regard to artificial intelligence. New to the Second Edition Fully revised and corrected throughout to bring the material up-to-date. Greater technical detail and exploration of basic mathematical concepts, while retaining the simplicity of explanation of the first edition. Entirely new chapters on large language models (LLMs), ChatGPT, and quantum computing.
Artificial Intelligence: An Introduction to the Big Ideas and their Development (Chapman & Hall/CRC Mathematics and Artificial Intelligence Series)
by Robert H. Chen Chelsea ChenArtificial Intelligence: An Introduction to Big Ideas and their Development, Second Edition guides readers through the history and development of artificial intelligence (AI), from its early mathematical beginnings through to the exciting possibilities of its potential future applications. To make this journey as accessible as possible, the authors build their narrative around accounts of some of the more popular and well-known demonstrations of artificial intelligence, including Deep Blue, AlphaGo and even Texas Hold’em, followed by their historical background, so that AI can be seen as a natural development of the mathematics and computer science of AI. As the book proceeds, more technical descriptions are presented at a pace that should be suitable for all levels of readers, gradually building a broad and reasonably deep understanding and appreciation for the basic mathematics, physics, and computer science that is rapidly developing artificial intelligence as it is today. Features Only mathematical prerequisite is an elementary knowledge of calculus. Accessible to anyone with an interest in AI and its mathematics and computer science. Suitable as a supplementary reading for a course in AI or the History of Mathematics and Computer Science in regard to artificial intelligence. New to the Second Edition Fully revised and corrected throughout to bring the material up-to-date. Greater technical detail and exploration of basic mathematical concepts, while retaining the simplicity of explanation of the first edition. Entirely new chapters on large language models (LLMs), ChatGPT, and quantum computing.
Artificial Intelligence: An Introduction for the Inquisitive Reader
by Robert H. Chen Chelsea C. ChenArtificial Intelligence: An Introduction for the Inquisitive Reader guides readers through the history and development of AI, from its early mathematical beginnings through to the exciting possibilities of its potential future applications. To make this journey as accessible as possible, the authors build their narrative around accounts of some of the more popular and well-known demonstrations of artificial intelligence including Deep Blue, AlphaGo and even Texas Hold’em, followed by their historical background, so that AI can be seen as a natural development of mathematics and computer science. As the book moves forward, more technical descriptions are presented at a pace that should be suitable for all levels of readers, gradually building a broad and reasonably deep understanding and appreciation for the basic mathematics, physics, and computer science that is rapidly developing artificial intelligence as it is today. Features Only mathematical prerequisite is an elementary knowledge of calculus Accessible to anyone with an interest in AI and its mathematics and computer science Suitable as a supplementary reading for a course in AI or the History of Mathematics and Computer Science in regard to artificial intelligence.
Artificial Intelligence: An Introduction for the Inquisitive Reader
by Robert H. Chen Chelsea C. ChenArtificial Intelligence: An Introduction for the Inquisitive Reader guides readers through the history and development of AI, from its early mathematical beginnings through to the exciting possibilities of its potential future applications. To make this journey as accessible as possible, the authors build their narrative around accounts of some of the more popular and well-known demonstrations of artificial intelligence including Deep Blue, AlphaGo and even Texas Hold’em, followed by their historical background, so that AI can be seen as a natural development of mathematics and computer science. As the book moves forward, more technical descriptions are presented at a pace that should be suitable for all levels of readers, gradually building a broad and reasonably deep understanding and appreciation for the basic mathematics, physics, and computer science that is rapidly developing artificial intelligence as it is today. Features Only mathematical prerequisite is an elementary knowledge of calculus Accessible to anyone with an interest in AI and its mathematics and computer science Suitable as a supplementary reading for a course in AI or the History of Mathematics and Computer Science in regard to artificial intelligence.
Artificial Intelligence (Studies in Systems, Decision and Control #517)
by Reem Khamis Hamdan Amina BuallayThe impact of artificial intelligence (AI) on business and society has been significant, with the incorporation of AI technologies such as robots, facial recognition, algorithms, and natural language processing into business leading to both corporate benefits and potential challenges for stakeholders. The question of how to engage in responsible business practices in the era of AI is an important one, and there is a need for more research on the relationship between AI and corporate social responsibility (CSR). As AI becomes more prevalent, there is a growing focus on the ethical implications of AI and the potential for AI to perpetuate biases or to displace human workers. CSR initiatives can include considerations of ethical AI in the development and use of AI systems. AI has the potential to solve many global challenges and improve people's lives, but it can also have negative consequences if not developed and used responsibly. CSR initiatives can focus on the social impact of AI,including efforts to ensure that the benefits of AI are distributed fairly and that AI is used for the common good. CSR initiatives often involve engaging with stakeholders, including employees, customers, and communities, to understand their needs and concerns and to ensure that their interests are taken into account. This can include engaging with stakeholders about the use of AI in the organization and its potential impactsThe adoption of AI in business is changing many aspects of doing business in a socially responsible manner, and there is a need to examine the potential unethical behaviors and novel ways of engaging in CSR that may arise. This book aims to focus on AI and CSR, and to advance our understanding of the role of AI in organizations and the literature on CSR by assembling high-quality papers with a strong connection between theory and practice.