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With the recent developments in computing technologies and the thriving research scene in Complexity Science, economists and other social scientists have become aware of a more flexible and promising alternative for modelling socioeconomic systems; one that, in contrast with neoclassical economics, advocates for the realism of the assumptions, the importance of context and culture, the heterogeneity of agents (individuals or organizations), and the bounded rationality of individuals who behave and learn in multifaceted ways in uncertain environments. The book synthesizes an extensive body of…mehr
With the recent developments in computing technologies and the thriving research scene in Complexity Science, economists and other social scientists have become aware of a more flexible and promising alternative for modelling socioeconomic systems; one that, in contrast with neoclassical economics, advocates for the realism of the assumptions, the importance of context and culture, the heterogeneity of agents (individuals or organizations), and the bounded rationality of individuals who behave and learn in multifaceted ways in uncertain environments. The book synthesizes an extensive body of work in the field of social complexity and constructs a unifying framework that allows developing concrete applications to important socioeconomic problems. This one-of-a-kind textbook provides a comprehensive panorama for advanced undergraduates and graduate students who want to become familiar with a wide range of issues related to social complexity. It is also a pioneering text that can support professors who wish to learn techniques and produce research in this novel field. Con los desarrollos recientes en las tecnologías de la computación y el floreciente dinamismo de las ciencias de la complejidad, economistas y otros científicos sociales tienen a su alcance una flexible y prometedora alternativa para la modelación de los sistemas socioeconómicos. Esta metodología, en contraste con la economía neoclásica, aboga por el realismo de los supuestos, la importancia del contexto y la cultura, la heterogeneidad de los agentes (individuos y organizaciones), y la racionalidad acotada de las personas que se comportan y aprenden de maneras muy diversas en entorno con incertidumbre. El libro sintetiza la extensa literatura que existe sobre la complejidad social, y construye un enfoque unificador que permite elaborar aplicaciones concretas con las que abordar importantes problemas socioeconómicos. Se trata de un texto singular dado que presenta un panorama comprensivo del campo de estudio, por lo que puede resultar de sumo interés para estudiante de licenciatura avanzados, y alumnos de posgrado que desean adentrarse en el tema. Asimismo, se trata de un texto pionero de gran utilidad para profesores y analistas interesados en aprender algunas de las técnicas del paradigma de la complejidad social para, de esta forma, aplicarlas en sus tareas de investigación.
Gonzalo Castañeda is a Mexican economist who holds a PhD from Cornell University and two BAs from the Mexican Autonomous Institute of Technology (ITAM). He currently works at the prestigious Centre for the Research and Teaching of Economics (CIDE) in Mexico City and is a member of the National System of Researchers (SNI, level III). He has been a visiting scholar in several universities and research centres in the United States and Europe: George Mason University (Virginia, USA), The Alan Turing Institute (London, UK), Sapienza University of Rome (Italy), International Institute for Applied System Analysis (Austria), University of Salamanca (Spain), and the Autonomous University of Barcelona (Spain). Dr Castañeda has been studying social complexity for more than 15 years. During this time, he has delivered various courses on the topic at graduate and undergraduate levels, leading to the creation of this book. His research has been conducted in different approaches of economic thinking including neoclassical, structural, institutional, and evolutionary.
Inhaltsangabe
Preface 1 Why study other paradigms? 2 Vision and modelling of complexity 3 The dynamics of social phenomena 4 Complexity in economic thought 5 Complexity and emerging properties 6 The self-organisation of complexity 7 Cellular automata 8 Homo Socialis 9 The multifaceted behaviour of human beings 10 Structure and its analytical instrumentation 11 Socioeconomic evolution 12 Agent-based computational models 13 Three examples of agent-based models 14 Computational models of networks 15 Topology and network formation processes 16 The dynamics of social diffusion 17 Learning in contexts of uncertainty 18 Introduction to genetic algorithms 19 Validation and social mechanisms 20 Calibration, verification and replication 21 Empirical applications of social complexity
Preface 1 Why study other paradigms? 2 Vision and modelling of complexity 3 The dynamics of social phenomena 4 Complexity in economic thought 5 Complexity and emerging properties 6 The self-organisation of complexity 7 Cellular automata 8 Homo Socialis 9 The multifaceted behaviour of human beings 10 Structure and its analytical instrumentation 11 Socioeconomic evolution 12 Agent-based computational models 13 Three examples of agent-based models 14 Computational models of networks 15 Topology and network formation processes 16 The dynamics of social diffusion 17 Learning in contexts of uncertainty 18 Introduction to genetic algorithms 19 Validation and social mechanisms 20 Calibration, verification and replication 21 Empirical applications of social complexity
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