Complex Systems In The Social And Behavioral Sciences

Complexity Systems in the Social and Behavioral Sciences provides a sophisticated yet accessible account of complexity science or complex systems research. Phenomena in the behavioral, social, and hard sciences all exhibit certain important similarities consistent with complex systems. These include the concept of emergence, sensitivity to initial conditions, and interactions between agents in a system that yield unanticipated, nonlinear outcomes. The topics discussed range from the implications for artificial intelligence and computing to questions about how to model complex systems through agent-based modeling, to complex phenomena exhibited in international relations, and in organizational behavior. This volume will be an invaluable addition for both the general reader and the specialist, offering new insights into this fascinating area of research.

Complexity systems are at the heart of behavior

This volume describes frontiers in social-behavioral modeling for contexts as diverse as national security, health, and on-line social gaming. Recent scientific and technological advances have created exciting opportunities for such improvements. However, the book also identifies crucial scientific, ethical, and cultural challenges to be met if social-behavioral modeling is to achieve its potential. Doing so will require new methods, data sources, and technology. The volume discusses these, including those needed to achieve and maintain high standards of ethics and privacy. The result should be a new generation of modeling that will advance science and, separately, aid decision-making on major social and security-related subjects despite the myriad uncertainties and complexities of social phenomena. Intended to be relatively comprehensive in scope, the volume balances theory-driven, data-driven, and hybrid approaches. The latter may be rapidly iterative, as when artificial-intelligence methods are coupled with theory-driven insights to build models that are sound, comprehensible and usable in new situations. With the intent of being a milestone document that sketches a research agenda for the next decade, the volume draws on the wisdom, ideas and suggestions of many noted researchers who draw in turn from anthropology, communications, complexity science, computer science, defense planning, economics, engineering, health systems, medicine, neuroscience, physics, political science, psychology, public policy and sociology. In brief, the volume discusses: Cutting-edge challenges and opportunities in modeling for social and behavioral science Special requirements for achieving high standards of privacy and ethics New approaches for developing theory while exploiting both empirical and computational data Issues of reproducibility, communication, explanation, and validation Special requirements for models intended to inform decision making about complex social systems

This volume in the Encyclopedia of Complexity and Systems Science, Second Edition, combines the main features of Game Theory, covering most of the fundamental theoretical aspects under the cooperative and non-cooperative approaches, with the procedures of Agent-Based Modeling for studying complex systems composed of a large number of interacting entities with many degrees of freedom. In Game Theory, the cooperative approach focuses on the possible outcomes of the decision-makers’ interaction by abstracting from the "rational" actions or decisions that may lead to these outcomes. The non-cooperative approach focuses on the actions that the decision-makers can take. As John von Neumann and Oskar Morgenstern argued in their path-breaking book of 1944 entitled Theory of Games and Economic Behavior, most economic questions should be analyzed as games. The models of game theory are abstract representations of a number of real-life situations and have applications to economics, political science, computer science, evolutionary biology, social psychology, and law among others. Agent-Based Modeling (ABM) is a relatively new computational modeling paradigm which aims to construct the computational counterpart of a conceptual model of the system under study on the basis of discrete entities (i.e., the agent) with some properties and behavioral rules, and then to simulate them in a computer to mimic the real phenomena. Given the relative immaturity of this modeling paradigm, and the broad spectrum of disciplines in which it is applied, a clear cut and widely accepted definition of high level concepts of agents, environment, interactions and so on, is still lacking. This volume explores the state-of-the-art in the development of a real ABM ontology to address the epistemological issues related to this emerging paradigm for modeling complex systems.

Describes contemporary approach to the modeling of complex cognitive and behavioral processes. This book provides examples of translational research ranging from clinical neuropsychology to self-actualization, from medical informatics to industrial psychology, from programmed learning to psychiatric rehabilitation.

Systems Research for Behavioral Science will be of interest to those in any discipline concerned with developments in science. It is addressed principally to the student of human behavior as that study is approached from the social side.Previously, the study of human behavior was the general area of science that had been slowest to respond to the exciting challenge of the modern systems outlook. Yet it is behavioral science that stands to gain the most from insights into the workings of more complex systems. The editor presents not only a fair selection of systems research in behavioral science, but also provides an extensive selection of important statements of general principles, including several already considered classics. Hence, this sourcebook may function in part as a principles text, exposing the initiate to original pioneering statements as well as later work inspired by them, and alerting the sizeable number of underexposed scholars who are over-familiar with the few terms such as feedback, boundary, input, and output, that there are much greater depths to plumb than meet the eye in semi-popular accounts of cybernetics. This volume is an overview of thinking that reflects a trend toward the system point of view. Some of the chapters are philosophical: they discuss the significance of the trend as a development in the contemporary philosophy of science. Some are inevitably detailed and technical. Still other chapters discuss the relevance of concepts that are central in the system approach, to particular fields of research. The picture that emerges is far from that of a unified theory. It is an open question whether much progress can be made by attempts to construct a "unified theory of systems" on some rigorous axiomatic base.

This pioneering text provides a comprehensive introduction to systems structure, function, and modeling as applied in all fields of science and engineering. Systems understanding is increasingly recognized as a key to a more holistic education and greater problem solving skills, and is also reflected in the trend toward interdisciplinary approaches to research on complex phenomena. While the concepts and components of systems science will continue to be distributed throughout the various disciplines, undergraduate degree programs in systems science are also being developed, including at the authors’ own institutions. However, the subject is approached, systems science as a basis for understanding the components and drivers of phenomena at all scales should be viewed with the same importance as a traditional liberal arts education. Principles of Systems Science contains many graphs, illustrations, side bars, examples, and problems to enhance understanding. From basic principles of organization, complexity, abstract representations, and behavior (dynamics) to deeper aspects such as the relations between information, knowledge, computation, and system control, to higher order aspects such as auto-organization, emergence and evolution, the book provides an integrated perspective on the comprehensive nature of systems. It ends with practical aspects such as systems analysis, computer modeling, and systems engineering that demonstrate how the knowledge of systems can be used to solve problems in the real world. Each chapter is broken into parts beginning with qualitative descriptions that stand alone for students who have taken intermediate algebra. The second part presents quantitative descriptions that are based on pre-calculus and advanced algebra, providing a more formal treatment for students who have the necessary mathematical background. Numerous examples of systems from every realm of life, including the physical and biological sciences, humanities, social sciences, engineering, pre-med and pre-law, are based on the fundamental systems concepts of boundaries, components as subsystems, processes as flows of materials, energy, and messages, work accomplished, functions performed, hierarchical structures, and more. Understanding these basics enables further understanding both of how systems endure and how they may become increasingly complex and exhibit new properties or characteristics. Serves as a textbook for teaching systems fundamentals in any discipline or for use in an introductory course in systems science degree programs Addresses a wide range of audiences with different levels of mathematical sophistication Includes open-ended questions in special boxes intended to stimulate integrated thinking and class discussion Describes numerous examples of systems in science and society Captures the trend towards interdisciplinary research and problem solving

In Complexity and Postmodernism, Paul Cilliers explores the idea of complexity in the light of contemporary perspectives from philosophy and science. Cilliers offers us a unique approach to understanding complexity and computational theory by integrating postmodern theory (like that of Derrida and Lyotard) into his discussion. Complexity and Postmodernism is an exciting and an original book that should be read by anyone interested in gaining a fresh understanding of complexity, postmodernism and connectionism.

Health professionals’ interest in social and behavioral science is rapidly increasing due to the growing recognition that social factors such as income, education, race, gender, and age all impact individuals’ health. These and other social conditions also shape patients’ illness experiences, the ways that they interact with health care providers, and the effectiveness of with which health professionals provide care. Understanding these social determinants and applying them to clinical practice is a major challenge for healthcare providers, which is why programs and accrediting bodies have been including more social and behavioral science content into the curricula for medical, nursing, and allied health programs. Social and Behavioral Science for Health Professionals provides in-depth coverage of the social determinants of health and how to directly apply these insights in clinical practice, thereby enhancing clinicians’ ability to engage their patients and more effectively render care. Broken into four parts, the book opens with the foundations of social science and health, including the shifting landscape of health and healthcare. The authors then cover the way in which social determinants of health shape large-scale features of health and illness in society, how they influence interactions between patients and providers in clinical settings, and how they shape health care systems and policies. Threshold concepts in each chapterfocus on conceptual and transformative learning while learning objectives, activities, and discussion questions provide instructors and students with robust sets of learning aids that intentionally focus on practical clinical, epidemiological, and policy issues. Ideal for students, educators, and professionals in health care, medical sociology, public health, and related fields, Social and Behavioral Science for Health Professionals is the only introduction available that clearly articulates why social and behavioral science matter in clinical care. New to This Edition: New Chapter 13 on Comparative Health Care Systems covers four models of health care systems and expands the global focus of the book Greater emphasis on the LGBTQ+ community provides coverage of how gender expression and sexual orientation influence health and quality of care received New coverage of current issues such as the opioid crisis and vaccine hesitancy that have been rendered especially important by the COVID-19 pandemic Added discussion questions at the end of every chapter strengthen students’ critical thinking skills and abilities to apply new insights to practical, real-world examples.

Society is complicated. But this book argues that this does not place it beyond the reach of a science that can help to explain and perhaps even to predict social behaviour. As a system made up of many interacting agents – people, groups, institutions and governments, as well as physical and technological structures such as roads and computer networks – society can be regarded as a complex system. In recent years, scientists have made great progress in understanding how such complex systems operate, ranging from animal populations to earthquakes and weather. These systems show behaviours that cannot be predicted or intuited by focusing on the individual components, but which emerge spontaneously as a consequence of their interactions: they are said to be ‘self-organized’. Attempts to direct or manage such emergent properties generally reveal that ‘top-down’ approaches, which try to dictate a particular outcome, are ineffectual, and that what is needed instead is a ‘bottom-up’ approach that aims to guide self-organization towards desirable states. This book shows how some of these ideas from the science of complexity can be applied to the study and management of social phenomena, including traffic flow, economic markets, opinion formation and the growth and structure of cities. Building on these successes, the book argues that the complex-systems view of the social sciences has now matured sufficiently for it to be possible, desirable and perhaps essential to attempt a grander objective: to integrate these efforts into a unified scheme for studying, understanding and ultimately predicting what happens in the world we have made. Such a scheme would require the mobilization and collaboration of many different research communities, and would allow society and its interactions with the physical environment to be explored through realistic models and large-scale data collection and analysis. It should enable us to find new and effective solutions to major global problems such as conflict, disease, financial instability, environmental despoliation and poverty, while avoiding unintended policy consequences. It could give us the foresight to anticipate and ameliorate crises, and to begin tackling some of the most intractable problems of the twenty-first century.