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Artificial economics is a computational approach that aims to explain economic systems by modeling them as societies of intelligent software agents. The individual agents make autonomous decisions, but their actual behaviors are constrained by available resources, other individuals' behaviors, and institutions. Intelligent software agents have communicative skills that enable simulation of negotiation, trade, reputation, and other forms of knowledge transfer that are at the basis of economic life. Incorporated learning mechanisms may adapt the agents' behaviors. In artificial economics, all system behavior is generated from the individual agents' simulated decisions; no system level laws are a priori imposed. For instance, price convergence and market clearing may emerge, but not necessarily. Thus, artificial economics facilitates the study of the mechanisms that make the economy function. This book presents a selection of peer-reviewed papers addressing recent developments in this field between economics and computer science.
"Digital Transformation in Healthcare 5.0: IoT, AI, and Digital Twin" provides a comprehensive overview of the integration of cutting-edge technology with healthcare, from the Fourth Industrial Revolution (4IR) to the introduction of IoT, AI, and Digital Twin technologies. This in-depth discussion of the digital revolution expanding the healthcare industry covers a wide range of topics, including digital disruption in healthcare delivery, the impact of 4IR and Health 4.0, e-health services and applications, virtual reality's impact on accessible healthcare delivery, digital twins and dietary health technologies, big data analytics in healthcare systems, machine learning models for cost-effective healthcare delivery systems, affordable healthcare with machine learning, enhanced biomedical signal processing with machine learning, and data-driven AI for information retrieval of biomedical images.
Blockchain for IoT provides the basic concepts of Blockchain technology and its applications to varied domains catering to socio-technical fields. It also introduces intelligent Blockchain platforms by way of infusing elements of computational intelligence into Blockchain technology. With the help of an interdisciplinary approach, it includes insights into real-life IoT applications to enable the readers to assimilate the concepts with ease. This book provides a balanced approach between theoretical understanding and practical applications. Features: A self-contained approach to integrating the principles of Blockchain with elements of computational intelligence A rich and novel foundation o...
This book constitutes the refereed proceedings of the 13th IFIP WG 5.11 International Symposium on Environmental Software Systems, ISESS 2020, held in Wageningen, The Netherlands, in February 2020. The 22 full papers and 3 short papers were carefully reviewed and selected from 29 submissions. The papers cover a wide range of topics on environmental informatics, including data mining, artificial intelligence, high performance and cloud computing, visualization and smart sensing for environmental, earth, agricultural and food applications.
This 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.
This book highlights recent developments in the field, presented at the Social Simulation 2015 conference in Groningen, The Netherlands. It covers advances both in applications and methods of social simulation. Societal issues addressed range across complexities in economic systems, opinion dynamics and civil violence, changing mobility patterns, different land-use, transition in the energy system, food production and consumption, ecosystem management and historical processes. Methodological developments cover how to use empirical data in validating models in general, formalization of behavioral theory in agent behavior, construction of artificial populations for experimentation, replication...
"Companies in food- and agribusiness chains and networks are facing ever-faster changes in the business environment, to which they must respond through continuous innovation. Societal concerns regarding animal welfare and environmental issues have to be met in a very competitive, increasingly global environment. The growing concern of consumers regarding the quality, traceability and environmental friendliness of products and processes call for fundamentally new ways of developing, producing and marketing products. New ways of organizing food supply networks, with new ties between firms and even between formerly separate sectors -such as the health and the food sector- are needed to cope with these new demands. This publication focusses on the dynamic response to these changes in chains and networks. Important topics include among others: critical success factors for design and control of innovative chains and networks, globalization of the business environment, effects of institutional and policy change, governance structures, technologies for managing interaction and design of information architectures for chains and networks."
Artificial economics aims to provide a generative approach to understanding problems in economics and social sciences. It is based on the consistent use of agent-based models and computational techniques. It encompasses a rich variety of techniques that generalize numerical analysis, mathematical programming, and micro-simulations. The peer-reviewed contributions in this volume address applications of artificial economics to markets and trading, auctions, networks, management, industry sectors, macroeconomics, and demographics and culture.
The field of artificial economics (AE) embraces a broad range of methodologies relying on computer simulations in order to model and study the complexity of economic and social phenomena. The overarching principle of AE is the analysis of aggregate properties of artificial economies populated by adaptive agents that are equipped with behavioural rules and specific individual targets. These aggregate properties are neither foreseen nor intended by the artificial agents; conversely they are emerging characteristics of such artificially simulated systems. The book presents a peer-reviewed collection of papers addressing a variety of issues related to macroeconomics, industrial organization, networks, management and finance, as well as purely methodological issues.