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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 system´s behavior.

Artificial intelligence --- Economics --- Self-organizing systems --- Economic aspects --- Data processing --- Economic theory --- Political economy --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Artificial intelligence. --- Game theory. --- Physics. --- Economic theory. --- Macroeconomics. --- Economics. --- Economic Theory/Quantitative Economics/Mathematical Methods. --- Game Theory, Economics, Social and Behav. Sciences. --- Artificial Intelligence (incl. Robotics). --- Complex Networks. --- Macroeconomics/Monetary Economics//Financial Economics. --- Social sciences --- Economic man --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Simulation methods --- Fifth generation computers --- Neural computers --- Mathematics. --- Artificial Intelligence. --- Applications of Graph Theory and Complex Networks. --- Math --- Science --- Natural philosophy --- Philosophy, Natural --- Physical sciences --- Dynamics --- Games, Theory of --- Theory of games --- Mathematical models --- Mathematics

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Der Osterreichische Wissenschaftstag widmete sich 2021 dem Thema "Modellbildung und Simulation in den Wissenschaften".Modelle sind vereinfachte Abbilder realer Zusammenhange und Entwicklungen. Insbesondere wenn sie mithilfe der Mathematik formuliert werden, dienen sie oft auch in Simulationen der Darstellung moglicher Entwicklungen der untersuchten Realobjekte, wo Experimente nicht moglich oder zu kostspielig sind. Dementsprechend sind Modellbildung und Simulation auch Gegenstande komplexer Diskurse und werfen eine Vielzahl an Fragen auf, die sich auch gerade aktuell im Rahmen der Covid-19 Pandemie stellen. Im Rahmen der Beitrage im 24. Band der Reihe "Wissenschaft-Bildung-Politik" wollen wir diese Fragen interdisziplinar diskutieren.

Science.