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Neoliberalism 2.0: A Pigovian Approach for 21st Century Markets
by L. NijsIn today's increasingly globalized environment, many economic fundamentals need to be reconsidered in order to regain stability in the global marketplace. One such consideration is the failing dynamics of the international tax infrastructure. Neoliberalism 2.0 brings a 21st century assessment of the Pigovian taxes, considering a completely new calibration of the international tax systems, inspired by the historically developed Pigovian tax model. The book considers the impact neoliberalism had and will have on regulatory infrastructure, democracy in an era of globalization and reduced legitimation of the national state. The Pigovian model brings home the often forgotten relationship between taxation (as a part of the regulatory sphere), macro-economics, and the political-philosophical context in which law and economics emerge. The model also takes into account the phenomena of globalization and financialization and is tested using the financial sector as an example. This book addresses the many challenges a Pigovian shift would imply for the sovereign and its national economies. Neoliberalism 2.0 demonstrates the ability to design a paradigm-changing alternative to the current tax infrastructure, while taking into account a low economic growth environment of the future, the implications of globalization and the changing relationship between citizens and their state.
Néron Models and Base Change
by Lars Halvard Halle Johannes NicaisePresentingthe first systematic treatment of the behavior of Néron models under ramifiedbase change, this book can be read as an introduction to various subtleinvariants and constructions related to Néron models of semi-abelian varieties,motivated by concrete research problems and complemented with explicitexamples. Néron models of abelian andsemi-abelian varieties have become an indispensable tool in algebraic andarithmetic geometry since Néron introduced them in his seminal 1964 paper. Applications range from the theory of heights in Diophantine geometry to Hodgetheory. We focus specifically on Néron component groups, Edixhoven's filtrationand the base change conductor of Chai and Yu, and we study these invariantsusing various techniques such as models of curves, sheaves on Grothendiecksites and non-archimedean uniformization. We then apply our results to thestudy of motivic zeta functions of abelian varieties. The final chaptercontains a list of challenging open questions. This book is aimed towardsresearchers with a background in algebraic and arithmetic geometry.
Nested Simulations: Theory and Application (Mathematische Optimierung und Wirtschaftsmathematik | Mathematical Optimization and Economathematics)
by Maximilian KleinMaximilian Klein analyses nested Monte Carlo simulations for the approximation of conditional expected values. Thereby, the book deals with two general risk functional classes for conditional expected values, on the one hand the class of moment-based estimators (notable examples are the probability of a large loss or the lower partial moments) and on the other hand the class of quantile-based estimators. For both functional classes, the almost sure convergence of the respective estimator is proven and the underlying convergence speed is quantified. In particular, the class of quantile-based estimators has important practical consequences especially for life insurance companies since the Value-at-Risk falls into this class and thus covers the solvency capital requirement problem. Furthermore, a novel non parametric confidence interval method for quantiles is presented which takes the additional noise of the inner simulation into account.
Netherlands Annual Review of Military Studies 2017
by Paul A.L. Ducheine Frans P.B. OsingaInternational conflict resolution increasingly involves the use of non-military power and non-kinetic capabilities alongside military capabilities in the face of hybrid threats. In this book, counter-measures to those threats are addressed by academics with both practical and theoretical experience and knowledge, providing strategic and operational insights into non-kinetic conflict resolution and on the use of power to influence, affect, deter or coerce states and non-state actors. This volume in the NL ARMS series deals with the non-kinetic capabilities to address international crises and conflicts and as always views matters from a global perspective. Included are chapters on the promise, practice and challenges of non-kinetic instruments of power, the instrumentality of soft power, information as a power instrument and manoeuvring in the information environment, Russia's use of deception and misinformation in conflict, applying counter-marketing techniques to fight ISIL, using statistics to profile terrorists, and employing tools such as Actor and Audience Analysis. Such diverse subjects as lawfare, the Law of Armed Conflict rules for non-kinetic cyber attacks, navigation warfare, GPS-spoofing, maritime interception operations, and finally, as a prerequisite, innovative ways for intelligence collection in UN Peacekeeping in Mali come up for discussion. The book will provide both professionals such as (foreign) policy makers and those active in the military services, academics at a master level and those with an interest in military law and the law of armed conflict with useful and up-to-date insights into the wide range of subjects that are contained within it. Paul A.L. Ducheine and Frans P.B. Osinga are General Officers and full professors at the Faculty of Military Sciences of the Netherlands Defence Academy in Breda, The Netherlands.
Network Algorithms, Data Mining, and Applications: NET, Moscow, Russia, May 2018 (Springer Proceedings in Mathematics & Statistics #315)
by Panos M. Pardalos Valery A. Kalyagin Oleg Prokopyev Ilya BychkovThis proceedings presents the result of the 8th International Conference in Network Analysis, held at the Higher School of Economics, Moscow, in May 2018. The conference brought together scientists, engineers, and researchers from academia, industry, and government. Contributions in this book focus on the development of network algorithms for data mining and its applications. Researchers and students in mathematics, economics, statistics, computer science, and engineering find this collection a valuable resource filled with the latest research in network analysis. Computational aspects and applications of large-scale networks in market models, neural networks, social networks, power transmission grids, maximum clique problem, telecommunication networks, and complexity graphs are included with new tools for efficient network analysis of large-scale networks. Machine learning techniques in network settings including community detection, clustering, and biclustering algorithms are presented with applications to social network analysis.
Network and Discrete Location
by Mark S. DaskinPraise for the First EditionThis book is refreshing to read since it takes an important topic... and presents it in a clear and concise manner by using examples that include visual presentations of the problem, solution methods, and results along with an explanation of the mathematical and procedural steps required to model the problem and work through to a solution." --Journal of ClassificationThoroughly updated and revised, Network and Discrete Location: Models, Algorithms, and Applications, Second Edition remains the go-to guide on facility location modeling. The book offers a unique introduction to methodological tools for solving location models and provides insight into when each approach is useful and what information can be obtained.The Second Edition focuses on real-world extensions of the basic models used in locating facilities, including production and distribution systems, location-inventory models, and defender-interdictor problems. A unique taxonomy of location problems and models is also presented. Featuring examples using the author's own software--SITATION, MOD-DIST, and MENU-OKF--as well as Microsoft Office® Excel®, the book provides: * A theoretical and applied perspective on location models and algorithms* An intuitive presentation of the uses and limits of modeling techniques* An introduction to integrated location-inventory modeling and defender-interdictor models for the design of reliable facility location systems* A full range of exercises to equip readers with an understanding of the basic facility location model types Network and Discrete Location: Models, Algorithms, and Applications, Second Edition is an essential resource for practitioners in applied and discrete mathematics, operations research, industrial engineering, and quantitative geography. The book is also a useful textbook for upper-level undergraduate, graduate, and MBA courses.
Network-Based Control of Unmanned Marine Vehicles
by Yu-Long Wang Qing-Long Han Chen Peng Lang MaThis book presents a comprehensive analysis of stability, stabilization, and fault detection in networked control systems, with a focus on unmanned marine vehicles. It investigates the challenges of network-based control in areas like heading control, fault detection filter and controller design, dynamic positioning, and cooperative target tracking. Communication networks in control systems can induce delays and dropouts, so the book presents the importance of stability analysis, stabilize, and fault detection. To help readers gain a deeper understanding of these concepts, the book provides fundamental concepts and real-world examples. This book is a valuable resource for researchers and practitioners working in the field of network-based control for unmanned marine vehicles.
Network Data Analytics: A Hands-on Approach For Application Development (Computer Communications and Networks)
by Srinidhi H. Siddesh G. M. K. G. SrinivasaIn order to carry out data analytics, we need powerful and flexible computing software. However the software available for data analytics is often proprietary and can be expensive. This book reviews Apache tools, which are open source and easy to use. After providing an overview of the background of data analytics, covering the different types of analysis and the basics of using Hadoop as a tool, it focuses on different Hadoop ecosystem tools, like Apache Flume, Apache Spark, Apache Storm, Apache Hive, R, and Python, which can be used for different types of analysis. It then examines the different machine learning techniques that are useful for data analytics, and how to visualize data with different graphs and charts. Presenting data analytics from a practice-oriented viewpoint, the book discusses useful tools and approaches for data analytics, supported by concrete code examples. The book is a valuable reference resource for graduate students and professionals in related fields, and is also of interest to general readers with an understanding of data analytics.
Network Economics and the Allocation of Savings
by Philipp ServatiusThis book provides a game theoretic model of interaction among VoIP telecommunications providers regarding their willingness to enter peering agreements with one another. The author shows that the incentive to peer is generally based on savings from otherwise payable long distance fees. At the same time, termination fees can have a countering and dominant effect, resulting in an environment in which VoIP firms decide against peering. Various scenarios of peering and rules for allocation of the savings are considered. The first part covers the relevant aspects of game theory and network theory, trying to give an overview of the concepts required in the subsequent application. The second part of the book introduces first a model of how the savings from peering can be calculated and then turns to the actual formation of peering relationships between VoIP firms. The conditions under which firms are willing to peer are then described, considering the possible influence of a regulatory body.
Network Games, Control, and Optimization
by Samson Lasaulce Tania Jimenez Eilon SolanThis contributed volume offers a collection of papers presented at the 2016 Network Games, Control, and Optimization conference (NETGCOOP), held at the University of Avignon in France, November 23-25, 2016. These papers highlight the increasing importance of network control and optimization in many networking application domains, such as mobile and fixed access networks, computer networks, social networks, transportation networks, and, more recently, electricity grids and biological networks. Covering a wide variety of both theoretical and applied topics in the areas listed above, the authors explore several conceptual and algorithmic tools that are needed for efficient and robust control operation, performance optimization, and better understanding the relationships between entities that may be acting cooperatively or selfishly in uncertain and possibly adversarial environments. As such, this volume will be of interest to applied mathematicians, computer scientists, engineers, and researchers in other related fields.
Network Games, Control and Optimization: 10th International Conference, NetGCooP 2020, France, September 22–24, 2021, Proceedings (Communications in Computer and Information Science #1354)
by Samson Lasaulce Panayotis Mertikopoulos Ariel OrdaThis book constitutes the conference proceedings of the 10th International Conference on Network Games, Control and Optimization, NETGCOOP 2020, held in Cargèse, Corsica, France, in September 2021*.The 12 full papers and 16 short papers were carefully reviewed and selected from 44 submissions. The papers are organized in the following topical sections: game theory and iterative algorithms applied to wireless communication; stochastic models for network performance analysis; game theory in mobile and wireless networks; scheduling and resource allocation problems in networks; advance in game theory; social network; electrical network.* The conference was postponed to 2021 due to the COVID-19 pandemic.
Network Games, Control, and Optimization: Proceedings Of Netgcoop 2016, Avignon, France (Static & Dynamic Game Theory: Foundations & Applications)
by Jean Walrand Quanyan Zhu Yezekael Hayel Tania JimenezThis contributed volume offers a collection of papers presented at the 2016 Network Games, Control, and Optimization conference (NETGCOOP), held at the University of Avignon in France, November 23-25, 2016. These papers highlight the increasing importance of network control and optimization in many networking application domains, such as mobile and fixed access networks, computer networks, social networks, transportation networks, and, more recently, electricity grids and biological networks. Covering a wide variety of both theoretical and applied topics in the areas listed above, the authors explore several conceptual and algorithmic tools that are needed for efficient and robust control operation, performance optimization, and better understanding the relationships between entities that may be acting cooperatively or selfishly in uncertain and possibly adversarial environments. As such, this volume will be of interest to applied mathematicians, computer scientists, engineers, and researchers in other related fields.
Network Geeks
by Brian E CarpenterThe impact on modern society made by the Internet is immeasurable. Yet some questioned "why anyone would want such a thing" when the idea was first introduced. Part history, part memoir and part cultural study, Network Geeks charts the creation of the Internet and the establishment of the Internet Engineering Task Force, from the viewpoint of a self-proclaimed geek who witnessed these developments first-hand. With boundless enthusiasm and abundant humour, Brian Carpenter leads the reader on a journey from post-war Britain to post-millennium New Zealand, describing how the Internet grew into today's ubiquitous, global network, including the genesis of the World-Wide Web in the hotbeds of a particle collider at CERN. Illuminating the science and technology behind the apparent "magic trick" of the Internet, Network Geeks opens a window into the initially bewildering world of the Internet engineering geek. After reading this book, you may wish to join this world yourself.
Network Graph Analysis and Visualization with Gephi
by Ken ChervenA practical, hands-on guide, that provides you with all the tools you need to visualize and analyze your data using network graphs with Gephi.This book is for data analysts who want to intuitively reveal patterns and trends, highlight outliers, and tell stories with their data using Gephi. It is great for anyone looking to explore interactions within network datasets, whether the data comes from social media or elsewhere. It is also a valuable resource for those seeking to learn more about Gephi without being overwhelmed by technical details.
Network Intelligence Meets User Centered Social Media Networks (Lecture Notes in Social Networks)
by Reda Alhajj H. Ulrich Hoppe Tobias Hecking Piotr Bródka Przemyslaw KazienkoThis edited volume presents advances in modeling and computational analysis techniques related to networks and online communities. It contains the best papers of notable scientists from the 4th European Network Intelligence Conference (ENIC 2017) that have been peer reviewed and expanded into the present format. The aim of this text is to share knowledge and experience as well as to present recent advances in the field. The book is a nice mix of basic research topics such as data-based centrality measures along with intriguing applied topics, for example, interaction decay patterns in online social communities. This book will appeal to students, professors, and researchers working in the fields of data science, computational social science, and social network analysis.
Network Meta-Analysis for Decision-Making
by Sofia Dias A. E. Ades Nicky J. Welton Jeroen P. Jansen Alexander J. SuttonA practical guide to network meta-analysis with examples and code In the evaluation of healthcare, rigorous methods of quantitative assessment are necessary to establish which interventions are effective and cost-effective. Often a single study will not provide the answers and it is desirable to synthesise evidence from multiple sources, usually randomised controlled trials. This book takes an approach to evidence synthesis that is specifically intended for decision making when there are two or more treatment alternatives being evaluated, and assumes that the purpose of every synthesis is to answer the question “for this pre-identified population of patients, which treatment is ‘best’?” A comprehensive, coherent framework for network meta-analysis (mixed treatment comparisons) is adopted and estimated using Bayesian Markov Chain Monte Carlo methods implemented in the freely available software WinBUGS. Each chapter contains worked examples, exercises, solutions and code that may be adapted by readers to apply to their own analyses. This book can be used as an introduction to evidence synthesis and network meta-analysis, its key properties and policy implications. Examples and advanced methods are also presented for the more experienced reader. Methods used throughout this book can be applied consistently: model critique and checking for evidence consistency are emphasised. Methods are based on technical support documents produced for NICE Decision Support Unit, which support the NICE Methods of Technology Appraisal. Code presented is also the basis for the code used by the ISPOR Task Force on Indirect Comparisons. Includes extensive carefully worked examples, with thorough explanations of how to set out data for use in WinBUGS and how to interpret the output. Network Meta-Analysis for Decision Making will be of interest to decision makers, medical statisticians, health economists, and anyone involved in Health Technology Assessment including the pharmaceutical industry.
Network Optimization
by V. BalakrishnanProblems in network optimization arise in all areas of technology and industrial management. The topic of network flows has applications in diverse fields such as chemistry, engineering, management science, scheduling and transportation, to name a few. Network Optimization introduces the subject to undergraduate and graduate students in computer science, mathematics and operations research. The focus is mainly on developing the mathematical underpinnings of the techniques that make it possible to solve the several optimization problems covered in the text. The text discusses such topics as optimal branching problems, transshipment problems, shortest path problems, minimum cost flow problems, maximum flow problems, matching in bipartite and nonbipartite graphs and many applications to combinatorics. Also included is a large number of exercises.
Network Optimization Methods in Passivity-Based Cooperative Control (Springer Theses)
by Miel SharfThis book establishes an important mathematical connection between cooperative control problems and network optimization problems. It shows that many cooperative control problems can in fact be understood, under certain passivity assumptions, using a pair of static network optimization problems. Merging notions from passivity theory and network optimization, it describes a novel network optimization approach that can be applied to the synthesis of controllers for diffusively-coupled networks of passive (or passivity-short) dynamical systems. It also introduces a data-based, model-free approach for the synthesis of network controllers for multi-agent systems with passivity-short agents. Further, the book describes a method for monitoring link faults in multi-agent systems using passivity theory and graph connectivity. It reports on some practical case studies describing the effectivity of the developed approaches in vehicle networks. All in all, this book offers an extensive source of information and novel methods in the emerging field of multi-agent cooperative control, paving the way to future developments of autonomous systems for various application domains
Network-Oriented Modeling
by Jan TreurThis book presents a new approach that can be applied to complex, integrated individual and social human processes. It provides an alternative means of addressing complexity, better suited for its purpose than and effectively complementing traditional strategies involving isolation and separation assumptions. Network-oriented modeling allows high-level cognitive, affective and social models in the form of (cyclic) graphs to be constructed, which can be automatically transformed into executable simulation models. The modeling format used makes it easy to take into account theories and findings about complex cognitive and social processes, which often involve dynamics based on interrelating cycles. Accordingly, it makes it possible to address complex phenomena such as the integration of emotions within cognitive processes of all kinds, of internal simulations of the mental processes of others, and of social phenomena such as shared understandings and collective actions. A variety of sample models - including those for ownership of actions, fear and dreaming, the integration of emotions in joint decision-making based on empathic understanding, and evolving social networks - illustrate the potential of the approach. Dedicated software is available to support building models in a conceptual or graphical manner, transforming them into an executable format and performing simulation experiments. The majority of the material presented has been used and positively evaluated by undergraduate and graduate students and researchers in the cognitive, social and AI domains. Given its detailed coverage, the book is ideally suited as an introduction for graduate and undergraduate students in many different multidisciplinary fields involving cognitive, affective, social, biological, and neuroscience domains.
Network Reliability: A Lecture Course (SpringerBriefs in Electrical and Computer Engineering)
by Ilya Gertsbakh Yoseph ShpunginThis introductory book equips the reader to apply the core concepts and methods of network reliability analysis to real-life problems. It explains the modeling and critical analysis of systems and probabilistic networks, and requires only a minimal background in probability theory and computer programming. Based on the lecture notes of eight courses taught by the authors, the book is also self-contained, with no theory needed beyond the lectures. The primary focus is on essential “modus operandi,” which are illustrated in numerous examples and presented separately from the more difficult theoretical material.
Network Science: An Aerial View
by Francesca Biagini Göran Kauermann Thilo Meyer-BrandisThis book provides an overview of network science from the perspective of diverse academic fields, offering insights into the various research areas within network science. The authoritative contributions on statistical network analysis, mathematical network science, genetic networks, Bayesian networks, network visualisation, and systemic risk in networks explore the main questions in the respective fields: What has been achieved to date? What are the research challenges and obstacles? What are the possible interconnections with other fields? And how can cross-fertilization between these fields be promoted? Network science comprises numerous scientific disciplines, including computer science, economics, mathematics, statistics, social sciences, bioinformatics, and medicine, among many others. These diverse research areas require and use different data-analytic and numerical methods as well as different theoretical approaches. Nevertheless, they all examine and describe interdependencies, associations, and relationships of entities in different kinds of networks. The book is intended for researchers as well as interested readers working in network science who want to learn more about the field – beyond their own research or work niche. Presenting network science from different perspectives without going into too much technical detail, it allows readers to gain an overview without having to be a specialist in any or all of these disciplines.
Network Science
by Desmond J. Higham Gian-Luca Oppo Ernesto Estrada Maria FoxNetwork Science is the emerging field concerned with the study of large, realistic networks. This interdisciplinary endeavor, focusing on the patterns of interactions that arise between individual components of natural and engineered systems, has been applied to data sets from activities as diverse as high-throughput biological experiments, online trading information, smart-meter utility supplies, and pervasive telecommunications and surveillance technologies. This unique text/reference provides a fascinating insight into the state of the art in network science, highlighting the commonality across very different areas of application and the ways in which each area can be advanced by injecting ideas and techniques from another. The book includes contributions from an international selection of experts, providing viewpoints from a broad range of disciplines. It emphasizes networks that arise in nature--such as food webs, protein interactions, gene expression, and neural connections--and in technology--such as finance, airline transport, urban development and global trade. Topics and Features: begins with a clear overview chapter to introduce this interdisciplinary field; discusses the classic network science of fixed connectivity structures, including empirical studies, mathematical models and computational algorithms; examines time-dependent processes that take place over networks, covering topics such as synchronisation, and message passing algorithms; investigates time-evolving networks, such as the World Wide Web and shifts in topological properties (connectivity, spectrum, percolation); explores applications of complex networks in the physical and engineering sciences, looking ahead to new developments in the field. Researchers and professionals from disciplines as varied as computer science, mathematics, engineering, physics, chemistry, biology, ecology, neuroscience, epidemiology, and the social sciences will all benefit from this topical and broad overview of current activities and grand challenges in the unfolding field of network science.
Network Science: Analysis and Optimization Algorithms for Real-World Applications
by Carlos Andre PinheiroNetwork Science Network Science offers comprehensive insight on network analysis and network optimization algorithms, with simple step-by-step guides and examples throughout, and a thorough introduction and history of network science, explaining the key concepts and the type of data needed for network analysis, ensuring a smooth learning experience for readers. It also includes a detailed introduction to multiple network optimization algorithms, including linear assignment, network flow and routing problems. The text is comprised of five chapters, focusing on subgraphs, network analysis, network optimization, and includes a list of case studies, those of which include influence factors in telecommunications, fraud detection in taxpayers, identifying the viral effect in purchasing, finding optimal routes considering public transportation systems, among many others. This insightful book shows how to apply algorithms to solve complex problems in real-life scenarios and shows the math behind these algorithms, enabling readers to learn how to develop them and scrutinize the results. Written by a highly qualified author with significant experience in the field, Network Science also includes information on: Sub-networks, covering connected components, bi-connected components, community detection, k-core decomposition, reach network, projection, nodes similarity and pattern matching Network centrality measures, covering degree, influence, clustering coefficient, closeness, betweenness, eigenvector, PageRank, hub and authority Network optimization, covering clique, cycle, linear assignment, minimum-cost network flow, maximum network flow problem, minimum cut, minimum spanning tree, path, shortest path, transitive closure, traveling salesman problem, vehicle routing problem and topological sort With in-depth and authoritative coverage of the subject and many case studies to convey concepts clearly, Network Science is a helpful training resource for professional and industry workers in, telecommunications, insurance, retail, banking, healthcare, public sector, among others, plus as a supplementary reading for an introductory Network Science course for undergraduate students.
Network Science In Education: Transformational Approaches in Teaching and Learning
by Catherine B. Cramer Mason A. Porter Hiroki Sayama Lori Sheetz Stephen Miles UzzoAround the globe, there is an increasingly urgent need to provide opportunities for learners to embrace complexity; to develop the many skills and habits of mind that are relevant to today's complex and interconnected world; and to make learning more connected to our rapidly changing workplace and society. This presents an opportunity to (1) leverage new paradigms for understanding the structure and function of teaching and learning communities, and (2) to promote new approaches to developing methods, curricular materials, and resources. Network science - the study of connectivity - can play an important role in these activities, both as an important subject in teaching and learning and as a way to develop interconnected curricula. Since 2010, an international community of network science researchers and educators has come together to raise the global level of network literacy by applying ideas from network science to teaching and learning. Network Science in Education - which refers to both this community and to its activities - has evolved in response to the escalating activity in the field of network science and the need for people to be able to access the field through education channels. Network Science In Education: Transformational Approaches in Teaching and Learning appeals to both instructors and professionals, while offering case studies from a wide variety of activities that have been developed around the globe: the creation of entirely new courses and degree programs; tools for K-20 learners, teachers, and the general public; and in-depth analysis of selected programs. As network-based pedagogy and the community of practice continues to grow, we hope that the book's readers will join this vibrant network education community to build on these nascent ideas and help deepen the understanding of networks for all learners.
Network Theory and Agent-Based Modeling in Economics and Finance
by Anindya S. Chakrabarti Lukáš Pichl Taisei KaizojiThis book presents the latest findings on network theory and agent-based modeling of economic and financial phenomena. In this context, the economy is depicted as a complex system consisting of heterogeneous agents that interact through evolving networks; the aggregate behavior of the economy arises out of billions of small-scale interactions that take place via countless economic agents. The book focuses on analytical modeling, and on the econometric and statistical analysis of the properties emerging from microscopic interactions. In particular, it highlights the latest empirical and theoretical advances, helping readers understand economic and financial networks, as well as new work on modeling behavior using rich, agent-based frameworks. Innovatively, the book combines observational and theoretical insights in the form of networks and agent-based models, both of which have proved to be extremely valuable in understanding non-linear and evolving complex systems. Given its scope, the book will capture the interest of graduate students and researchers from various disciplines (e.g. economics, computer science, physics, and applied mathematics) whose work involves the domain of complexity theory.