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An Integrated Approach to Home Security and Safety Systems
by Sonali Goyal Neera BatraThis book provides an integrated solution for security and safety in the home, covering both assistance in health monitoring and safety from strangers/intruders who want to enter the home with harmful intentions. It defines a system whereby recognition of a person/stranger at the door is done using three modules: Face Recognition, Voice Recognition and Similarity Index. These three modules are taken together to provide a percentage likelihood that the individual is in the "known" or "unknown" category. The system can also continuously monitor the health parameters of a vulnerable person living alone at home and aid them in calling for help in an emergency. The authors have analyzed a number of existing biometric techniques to provide security for an individual living alone at home. These biometric techniques have been tested using MATLAB® image processing and signal processing toolboxes, and results have been calculated on the basis of recognition rate. A major contribution in providing security is a hybrid algorithm proposed by the author named PICA, which combines features of both PCA (Principle Component Analysis) and ICA (Independent Component Analysis) algorithms. This hybrid approach gives better performance recognition than either system alone. The second proposed hybrid algorithm for voice recognition is named as a MFRASTA algorithm by combining features of MFCC (Mel Frequency Cepstral Coefficient) and RASTA-PLP (RelAtive SpecTrA-Perceptual Linear Prediction) algorithm. After performing experiments, results are collected on the basis of recognition rate. The authors have also proposed a third technique named as a Similarity Index to provide trust-based security for an individual. This technique is text independent in which a person is recognized by pronunciation, frequency, tone, pitch, etc., irrespective of the content spoken by the person. By combining these three techniques, a high recognition rate is provided to the person at the door and high security to the individual living independently at home. In the final contribution, the authors have proposed a fingertip-based application for health monitoring by using the concept of sensors. This application is developed using iPhone 6’s camera. When a person puts their fingertip on a camera lens, with the help of brightness of the skin, the person’s heartbeat will be monitored. This is possible even with a low-quality camera. In case of any emergency, text messages will be sent to the family members of the individual living alone by using 3G Dongle and MATLAB tool. Results show that the proposed work outperforms all the existing techniques used in face recognition, voice recognition, and health monitoring alone.
An Integrated Approach to Modeling and Optimization in Engineering and Science
by Levent Aydin Melih SavranAn Integrated Approach to Modeling and Optimization in Engineering and Science examines the effects of experimental design, mathematical modeling, and optimization processes for solving many different problems. The Experimental Design Method, Central Composite, Full Factorial, Taguchi, Box-Behnken, and D-Optimal methods are used, and the effects of the datasets obtained by these methods on mathematical modeling are investigated.This book will help graduates and senior undergraduates in courses on experimental design, modeling, optimization, and interdisciplinary engineering studies. It will also be of interest to research and development engineers and professionals working in scientific institutions based on design, modeling, and optimization.
An Integrated Framework for Energy-Economy-Emissions Modeling: A Case Study of India (SpringerBriefs in Environmental Science)
by Tejal KanitkarThis book combines three different energy-economy-emissions modeling methodologies into one Integrated Modeling Framework (IMF) in an attempt to fill gaps in current modeling research as it applies to developing countries. Through the analysis of existing mathematical models, including large macro-economic models and technology-explicit energy models, the work proposes planning methodologies for developing countries that face challenges on their economy and infrastructure due to climate change. The three modeling methodologies discussed in the chapters are a decomposition analysis of trends in emissions intensity of GDP, linear programming techniques to determine optimum energy supply pathways given various resource and emissions constraints, and an input-output analysis to evaluate the impact of energy policies on income and equity. After a brief introduction to the history of the development of energy studies and the linkages between energy, economic, and environmental systems, the book delves into the component methodologies of the IMF and their intended outcomes. The decomposition analysis is intended to gauge the energy intensity of GDP and the structural composition of the economy to provide a basis on which scenarios are constructed in the following two methodologies. The linear programs are meant to develop a methodology to determine energy options under a variety of scenarios that capture the technical and economic characteristics of the power sector of developing countries. Lastly, the input-output analysis aims to build a methodology through which energy policy decisions can be understood and quantified to ensure the best possible impacts on developing economies and societies. Those who will be interested in this book include policy makers, academics, and students and professionals working on energy studies and energy-economy modeling.
An Integrated Introduction to Computer Graphics and Geometric Modeling (Chapman & Hall/CRC Computer Graphics, Geometric Modeling, and Animation Series)
by Ronald GoldmanTaking a novel, more appealing approach than current texts, An Integrated Introduction to Computer Graphics and Geometric Modeling focuses on graphics, modeling, and mathematical methods, including ray tracing, polygon shading, radiosity, fractals, freeform curves and surfaces, vector methods, and transformation techniques. The author begins with f
An Intelligence in Our Image: The Risks of Bias and Errors in Artificial Intelligence
by William Welser Iv Osonde A. OsobaMachine learning algorithms and artificial intelligence influence many aspects of life today and have gained an aura of objectivity and infallibility. The use of these tools introduces a new level of risk and complexity in policy. This report illustrates some of the shortcomings of algorithmic decisionmaking, identifies key themes around the problem of algorithmic errors and bias, and examines some approaches for combating these problems.
An Intelligent Customer Complaint Management System with Application to the Transport and Logistics Industry (Springer Theses)
by Alireza FaedThis thesis addresses the issue of customer complaints in the context of Customer Relationship Management (CRM). After a comprehensive survey of the current literature on CRM, the thesis describes the development of a new intelligent CRM (I-CRM) framework, which integrates text analytics, type mapping, SPSS, structural equation modeling, and linear and fuzzy approaches. This new methodology, in contrast to previous ones, is able to handle customer complaints with respect to different variables, thus allowing organizations to find their key customers and key complaints, and to address and provide solution to the major complaints of the key customers, hence promoting business development. The thesis also describes the successful application of the method to a real-world case, represented by the immeasurable truck drivers complaints at the Fremantle port in Western Australia.
An Intelligent Inspection Planning System for Prismatic Parts on CMMs
by Vidosav D. Majstorović Slavenko M. StojadinovićThis book examines an intelligent system for the inspection planning of prismatic parts on coordinate measuring machines (CMMs). The content focuses on four main elements: the engineering ontology, the model of inspection planning for prismatic parts on CMMs, the optimisation model of the measuring path based on an ant-colony approach, and the model of probe configuration and setup planning based on a genetic algorithm. The model of inspection planning for CMMs developed here addresses inspection feature construction, the sampling strategy, probe accessibility analysis, automated collision-free operation, and probe path planning. The proposed model offers a novel approach to intelligent inspection, while also minimizing human involvement (and thus the risk of human error) through intelligent planning of the probe configuration and part setup. The advantages of this approach include: reduced preparation times due to the automatic generation of a measuring protocol; potential optimisation of the measuring probe path, i.e., less time needed for the actual measurement; and increased planning process autonomy through minimal human involvement in the setup analysis and probe configuration.
An Interdisciplinary Approach to Modern Network Security
by Dac-Nhuong Le Surbhi Bhatia Sabyasachi Pramanik Anand SharmaAn Interdisciplinary Approach to Modern Network Security presents the latest methodologies and trends in detecting and preventing network threats. Investigating the potential of current and emerging security technologies, this publication is an all-inclusive reference source for academicians, researchers, students, professionals, practitioners, network analysts and technology specialists interested in the simulation and application of computer network protection. It presents theoretical frameworks and the latest research findings in network security technologies, while analyzing malicious threats which can compromise network integrity. It discusses the security and optimization of computer networks for use in a variety of disciplines and fields. Touching on such matters as mobile and VPN security, IP spoofing and intrusion detection, this edited collection emboldens the efforts of researchers, academics and network administrators working in both the public and private sectors. This edited compilation includes chapters covering topics such as attacks and countermeasures, mobile wireless networking, intrusion detection systems, next-generation firewalls, web security and much more. Information and communication systems are an essential component of our society, forcing us to become dependent on these infrastructures. At the same time, these systems are undergoing a convergence and interconnection process that has its benefits, but also raises specific threats to user interests. Citizens and organizations must feel safe when using cyberspace facilities in order to benefit from its advantages. This book is interdisciplinary in the sense that it covers a wide range of topics like network security threats, attacks, tools and procedures to mitigate the effects of malware and common network attacks, network security architecture and deep learning methods of intrusion detection.
An Internet for the People: The Politics and Promise of craigslist (Princeton Studies in Culture and Technology #26)
by Professor Jessa LingelHow craigslist champions openness, democracy, and other vanishing principles of the early webBegun by Craig Newmark as an e-mail to some friends about cool events happening around San Francisco, craigslist is now the leading classifieds service on the planet. It is also a throwback to the early internet. The website has barely seen an upgrade since it launched in 1996. There are no banner ads. The company doesn't profit off your data. An Internet for the People explores how people use craigslist to buy and sell, find work, and find love—and reveals why craigslist is becoming a lonely outpost in an increasingly corporatized web.Drawing on interviews with craigslist insiders and ordinary users, Jessa Lingel looks at the site's history and values, showing how it has mostly stayed the same while the web around it has become more commercial and far less open. She examines craigslist's legal history, describing the company's courtroom battles over issues of freedom of expression and data privacy, and explains the importance of locality in the social relationships fostered by the site. More than an online garage sale, job board, or dating site, craigslist holds vital lessons for the rest of the web. It is a website that values user privacy over profits, ease of use over slick design, and an ethos of the early web that might just hold the key to a more open, transparent, and democratic internet.
An Internet in Your Head: A New Paradigm for How the Brain Works
by Daniel GrahamWhether we realize it or not, we think of our brains as computers. In neuroscience, the metaphor of the brain as a computer has defined the field for much of the modern era. But as neuroscientists increasingly reevaluate their assumptions about how brains work, we need a new metaphor to help us ask better questions.The computational neuroscientist Daniel Graham offers an innovative paradigm for understanding the brain. He argues that the brain is not like a single computer—it is a communication system, like the internet. Both are networks whose power comes from their flexibility and reliability. The brain and the internet both must route signals throughout their systems, requiring protocols to direct messages from just about any point to any other. But we do not yet understand how the brain manages the dynamic flow of information across its entire network. The internet metaphor can help neuroscience unravel the brain’s routing mechanisms by focusing attention on shared design principles and communication strategies that emerge from parallel challenges. Highlighting similarities between brain connectivity and the architecture of the internet can open new avenues of research and help unlock the brain’s deepest secrets.An Internet in Your Head presents a clear-eyed and engaging tour of brain science as it stands today and where the new paradigm might take it next. It offers anyone with an interest in brains a transformative new way to conceptualize what goes on inside our heads.
An Introduction To Artificial Intelligence
by Janet FinlayAn authoritative and accessible one-stop resource, An Introduction to Artificial Intelligence presents the first full examination of AI. Designed to provide an understanding of the foundations of artificial intelligence, it examines the central computational techniques employed by AI, including knowledge representation, search, reasoning, and learning, as well as the principal application domains of expert systems, natural language, vision, robotics, software agents and cognitive modeling. Many of the major philosophical and ethical issues of AI are also introduced.Throughout the volume, the authors provide detailed, well-illustrated treatments of each topic with abundant examples and exercises. The authors bring this exciting field to life by presenting a substantial and robust introduction to artificial intelligence in a clear and concise coursebook form. This book stands as a core text for all computer scientists approaching AI for the first time.
An Introduction to Agent-Based Modeling: Modeling Natural, Social, and Engineered Complex Systems with NetLogo
by Uri Wilensky William RandThe advent of widespread fast computing has enabled us to work on more complex problems and to build and analyze more complex models. This book provides an introduction to one of the primary methodologies for research in this new field of knowledge. Agent-based modeling (ABM) offers a new way of doing science: by conducting computer-based experiments. ABM is applicable to complex systems embedded in natural, social, and engineered contexts, across domains that range from engineering to ecology. An Introduction to Agent-Based Modeling offers a comprehensive description of the core concepts, methods, and applications of ABM. Its hands-on approach -- with hundreds of examples and exercises using NetLogo -- enables readers to begin constructing models immediately, regardless of experience or discipline.The book first describes the nature and rationale of agent-based modeling, then presents the methodology for designing and building ABMs, and finally discusses how to utilize ABMs to answer complex questions. Features in each chapter include step-by-step guides to developing models in the main text; text boxes with additional information and concepts; end-of-chapter explorations; and references and lists of relevant reading. There is also an accompanying website with all the models and code.
An Introduction to Agent-Based Modeling: Modeling Natural, Social, and Engineered Complex Systems with NetLogo
by Uri Wilensky William RandA comprehensive and hands-on introduction to the core concepts, methods, and applications of agent-based modeling, including detailed NetLogo examples. The advent of widespread fast computing has enabled us to work on more complex problems and to build and analyze more complex models. This book provides an introduction to one of the primary methodologies for research in this new field of knowledge. Agent-based modeling (ABM) offers a new way of doing science: by conducting computer-based experiments. ABM is applicable to complex systems embedded in natural, social, and engineered contexts, across domains that range from engineering to ecology. An Introduction to Agent-Based Modeling offers a comprehensive description of the core concepts, methods, and applications of ABM. Its hands-on approach—with hundreds of examples and exercises using NetLogo—enables readers to begin constructing models immediately, regardless of experience or discipline. The book first describes the nature and rationale of agent-based modeling, then presents the methodology for designing and building ABMs, and finally discusses how to utilize ABMs to answer complex questions. Features in each chapter include step-by-step guides to developing models in the main text; text boxes with additional information and concepts; end-of-chapter explorations; and references and lists of relevant reading. There is also an accompanying website with all the models and code.
An Introduction to Analytical Fuzzy Plane Geometry (Studies in Fuzziness and Soft Computing #381)
by Debdas Ghosh Debjani ChakrabortyThis book offers a rigorous mathematical analysis of fuzzy geometrical ideas. It demonstrates the use of fuzzy points for interpreting an imprecise location and for representing an imprecise line by a fuzzy line. Further, it shows that a fuzzy circle can be used to represent a circle when its description is not known precisely, and that fuzzy conic sections can be used to describe imprecise conic sections. Moreover, it discusses fundamental notions on fuzzy geometry, including the concepts of fuzzy line segment and fuzzy distance, as well as key fuzzy operations, and includes several diagrams and numerical illustrations to make the topic more understandable. The book fills an important gap in the literature, providing the first comprehensive reference guide on the fuzzy mathematics of imprecise image subsets and imprecise geometrical objects. Mainly intended for researchers active in fuzzy optimization, it also includes chapters relevant for those working on fuzzy image processing and pattern recognition. Furthermore, it is a valuable resource for beginners interested in basic operations on fuzzy numbers, and can be used in university courses on fuzzy geometry, dealing with imprecise locations, imprecise lines, imprecise circles, and imprecise conic sections.
An Introduction to Applied Electromagnetics and Optics
by Vladimir V. Mitin Dmitry I. SementsovModern technology is rapidly developing and for this reason future engineers need to acquire advanced knowledge in science and technology, including electromagnetic phenomena. This book is a contemporary text of a one-semester course for junior electrical engineering students. It covers a broad spectrum of electromagnetic phenomena such as, surface waves, plasmas, photonic crystals, negative refraction as well as related materials including superconductors. In addition, the text brings together electromagnetism and optics as the majority of texts discuss electromagnetism disconnected from optics. In contrast, in this book both are discussed. Seven labs have been developed to accompany the material of the book.
An Introduction to Artificial Intelligence Based on Reproducing Kernel Hilbert Spaces (Compact Textbooks in Mathematics)
by Sergei PereverzyevThis textbook provides an in-depth exploration of statistical learning with reproducing kernels, an active area of research that can shed light on trends associated with deep neural networks. The author demonstrates how the concept of reproducing kernel Hilbert Spaces (RKHS), accompanied with tools from regularization theory, can be effectively used in the design and justification of kernel learning algorithms, which can address problems in several areas of artificial intelligence. Also provided is a detailed description of two biomedical applications of the considered algorithms, demonstrating how close the theory is to being practically implemented. Among the book’s several unique features is its analysis of a large class of algorithms of the Learning Theory that essentially comprise every linear regularization scheme, including Tikhonov regularization as a specific case. It also provides a methodology for analyzing not only different supervised learning problems, such as regression or ranking, but also different learning scenarios, such as unsupervised domain adaptation or reinforcement learning. By analyzing these topics using the same theoretical framework, rather than approaching them separately, their presentation is streamlined and made more approachable.An Introduction to Artificial Intelligence Based on Reproducing Kernel Hilbert Spaces is an ideal resource for graduate and postgraduate courses in computational mathematics and data science.
An Introduction to Artificial Intelligence in Education (Bridging Human and Machine: Future Education with Intelligence)
by Shengquan Yu Yu LuThis book systematically reviews a broad range of cases in education that utilize cutting-edge AI technologies. Furthermore, it introduces readers to the latest findings on the scope of AI in education, so as to inspire researchers from non-technological fields (e.g. education, psychology and neuroscience) to solve education problems using the latest AI techniques. It also showcases a number of established AI systems and products that have been employed for education. Lastly, the book discusses how AI can offer an enabling technology for critical aspects of education, typically including the learner, content, strategy, tools and environment, and what breakthroughs and advances the future holds.The book provides an essential resource for researchers, students and industrial practitioners interested and engaged in the fields of AI and education. It also offers a convenient handbook for non-professional readers who need a primer on AI in education, and who want to gain a deeper understanding of emerging trends in this domain.
An Introduction to Artificial Psychology: Application Fuzzy Set Theory and Deep Machine Learning in Psychological Research using R
by Peter Watson Sara Saljoughi Hojjatollah Farahani Marija Blagojević Parviz Azadfallah Forough EsrafilianArtificial Psychology (AP) is a highly multidisciplinary field of study in psychology. AP tries to solve problems which occur when psychologists do research and need a robust analysis method. Conventional statistical approaches have deep rooted limitations. These approaches are excellent on paper but often fail to model the real world. Mind researchers have been trying to overcome this by simplifying the models being studied. This stance has not received much practical attention recently. Promoting and improving artificial intelligence helps mind researchers to find a holistic model of mental models. This development achieves this goal by using multiple perspectives and multiple data sets together with interactive, and realistic models. In this book, the methodology of approximate inference in psychological research from a theoretical and practical perspective has been considered. Quantitative variable-oriented methodology and qualitative case-oriented methods are both used to explain the set-oriented methodology and this book combines the precision of quantitative methods with information from qualitative methods. This is a book that many researchers can use to expand and deepen their psychological research and is a book which can be useful to postgraduate students. The reader does not need an in-depth knowledge of mathematics or statistics because statistical and mathematical intuitions are key here and they will be learned through practice. What is important is to understand and use the new application of the methods for finding new, dynamic and realistic interpretations. This book incorporates theoretical fuzzy inference and deep machine learning algorithms in practice. This is the kind of book that we wished we had had when we were students. This book covers at least some of the most important issues in mind research including uncertainty, fuzziness, continuity, complexity and high dimensionality which are inherent to mind data. These are elements of artificial psychology. This book implements models using R software.
An Introduction to Audio Content Analysis: Music Information Retrieval Tasks and Applications
by Alexander LerchAn Introduction to Audio Content Analysis Enables readers to understand the algorithmic analysis of musical audio signals with AI-driven approaches An Introduction to Audio Content Analysis serves as a comprehensive guide on audio content analysis explaining how signal processing and machine learning approaches can be utilized for the extraction of musical content from audio. It gives readers the algorithmic understanding to teach a computer to interpret music signals and thus allows for the design of tools for interacting with music. The work ties together topics from audio signal processing and machine learning, showing how to use audio content analysis to pick up musical characteristics automatically. A multitude of audio content analysis tasks related to the extraction of tonal, temporal, timbral, and intensity-related characteristics of the music signal are presented. Each task is introduced from both a musical and a technical perspective, detailing the algorithmic approach as well as providing practical guidance on implementation details and evaluation. To aid in reader comprehension, each task description begins with a short introduction to the most important musical and perceptual characteristics of the covered topic, followed by a detailed algorithmic model and its evaluation, and concluded with questions and exercises. For the interested reader, updated supplemental materials are provided via an accompanying website. Written by a well-known expert in the music industry, sample topics covered in Introduction to Audio Content Analysis include: Digital audio signals and their representation, common time-frequency transforms, audio features Pitch and fundamental frequency detection, key and chord Representation of dynamics in music and intensity-related features Beat histograms, onset and tempo detection, beat histograms, and detection of structure in music, and sequence alignment Audio fingerprinting, musical genre, mood, and instrument classification An invaluable guide for newcomers to audio signal processing and industry experts alike, An Introduction to Audio Content Analysis covers a wide range of introductory topics pertaining to music information retrieval and machine listening, allowing students and researchers to quickly gain core holistic knowledge in audio analysis and dig deeper into specific aspects of the field with the help of a large amount of references.
An Introduction to Bayesian Inference, Methods and Computation
by Nick HeardThese lecture notes provide a rapid, accessible introduction to Bayesian statistical methods. The course covers the fundamental philosophy and principles of Bayesian inference, including the reasoning behind the prior/likelihood model construction synonymous with Bayesian methods, through to advanced topics such as nonparametrics, Gaussian processes and latent factor models. These advanced modelling techniques can easily be applied using computer code samples written in Python and Stan which are integrated into the main text. Importantly, the reader will learn methods for assessing model fit, and to choose between rival modelling approaches.
An Introduction to Bioinformatics Algorithms (Computational Molecular Biology)
by Neil C. Jones Pavel A. PevznerAn introductory text that emphasizes the underlying algorithmic ideas that are driving advances in bioinformatics.This introductory text offers a clear exposition of the algorithmic principles driving advances in bioinformatics. Accessible to students in both biology and computer science, it strikes a unique balance between rigorous mathematics and practical techniques, emphasizing the ideas underlying algorithms rather than offering a collection of apparently unrelated problems. The book introduces biological and algorithmic ideas together, linking issues in computer science to biology and thus capturing the interest of students in both subjects. It demonstrates that relatively few design techniques can be used to solve a large number of practical problems in biology, and presents this material intuitively. An Introduction to Bioinformatics Algorithms is one of the first books on bioinformatics that can be used by students at an undergraduate level. It includes a dual table of contents, organized by algorithmic idea and biological idea; discussions of biologically relevant problems, including a detailed problem formulation and one or more solutions for each; and brief biographical sketches of leading figures in the field. These interesting vignettes offer students a glimpse of the inspirations and motivations for real work in bioinformatics, making the concepts presented in the text more concrete and the techniques more approachable.PowerPoint presentations, practical bioinformatics problems, sample code, diagrams, demonstrations, and other materials can be found at the Author's website.
An Introduction to Cellular Network Analysis Using Stochastic Geometry (Synthesis Lectures on Learning, Networks, and Algorithms)
by Harpreet S. Dhillon Jeffrey G. Andrews Abhishek K. Gupta Ahmad AlammouriThis book provides an accessible yet rigorous first reference for readers interested in learning how to model and analyze cellular network performance using stochastic geometry. In addition to the canonical downlink and uplink settings, analyses of heterogeneous cellular networks and dense cellular networks are also included. For each of these settings, the focus is on the calculation of coverage probability, which gives the complementary cumulative distribution function (ccdf) of signal-to-interference-and-noise ratio (SINR) and is the complement of the outage probability. Using this, other key performance metrics, such as the area spectral efficiency, are also derived. These metrics are especially useful in understanding the effect of densification on network performance. In order to make this a truly self-contained reference, all the required background material from stochastic geometry is introduced in a coherent and digestible manner.This Book:Provides an approachable introduction to the analysis of cellular networks and illuminates key system dependenciesFeatures an approach based on stochastic geometry as applied to cellular networks including both downlink and uplinkFocuses on the statistical distribution of signal-to-interference-and-noise ratio (SINR) and related metrics
An Introduction to Clustering with R (Behaviormetrics: Quantitative Approaches to Human Behavior #1)
by Maria Brigida Ferraro Paolo Giordani Francesca MartellaThe purpose of this book is to thoroughly prepare the reader for applied research in clustering. Cluster analysis comprises a class of statistical techniques for classifying multivariate data into groups or clusters based on their similar features. Clustering is nowadays widely used in several domains of research, such as social sciences, psychology, and marketing, highlighting its multidisciplinary nature. This book provides an accessible and comprehensive introduction to clustering and offers practical guidelines for applying clustering tools by carefully chosen real-life datasets and extensive data analyses. The procedures addressed in this book include traditional hard clustering methods and up-to-date developments in soft clustering. Attention is paid to practical examples and applications through the open source statistical software R. Commented R code and output for conducting, step by step, complete cluster analyses are available. The book is intended for researchers interested in applying clustering methods. Basic notions on theoretical issues and on R are provided so that professionals as well as novices with little or no background in the subject will benefit from the book.
An Introduction to Cognitive Economics: The Science of Mistakes
by Andrew CaplinThis book introduces readers to “cognitive economics,” a rapidly emerging interdisciplinary science built on economic, psychological, and data scientific foundations. Throughout the book, economist Andrew Caplin provides new approaches to help scholars collaborate and solve problems that can shape economic outcomes and bridge the gap between theoretical knowledge and the real world. Divided into two parts, the first section brings readers up to speed on economic concepts that underlie decision-making mistakes, such as utility functions, subjective beliefs, and costs of learning. It also explores real-world applications, including improvements in legal decision-making, online privacy protection, and optimizing human-AI collaboration. The book also discusses the future impact of AI on the workforce and emphasizes the need for decision-making skills and financial literacy in navigating this evolving landscape. In the second section of the book, Caplin addresses the barriers to progress within social sciences, advocating for interdisciplinary cooperation and innovative measurement techniques to advance the field. The book invites readers to contribute to the development of cognitive economics. Whether you are a socially-conscious and hard-working citizen, business leader, scholar, or policymaker, this book will help you understand why cognitive economics matters to you and how you can contribute to its takeoff. This book is available open access, which means it is freely available online.
An Introduction to Complex Systems: Making Sense of a Changing World
by Joe TranquilloThis book explores the interdisciplinary field of complex systems theory. By the end of the book, readers will be able to understand terminology that is used in complex systems and how they are related to one another; see the patterns of complex systems in practical examples; map current topics, in a variety of fields, to complexity theory; and be able to read more advanced literature in the field. The book begins with basic systems concepts and moves on to how these simple rules can lead to complex behavior. The author then introduces non-linear systems, followed by pattern formation, and networks and information flow in systems. Later chapters cover the thermodynamics of complex systems, dynamical patterns that arise in networks, and how game theory can serve as a framework for decision making. The text is interspersed with both philosophical and quantitative arguments, and each chapter ends with questions and prompts that help readers make more connections.