Titlebook: Complexity and Artificial Markets; Klaus Schredelseker,Florian Hauser Book 2008 Springer-Verlag Berlin Heidelberg 2008 Agent-based Modelli

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Abstract Interpretation of Indexed Grammars Social and Human Sciences. Two particular domain of interest are to compare ABM and simulations (Model To Model) within a given academic field or across different disciplines and to use ontology for to discuss about the epistemic and methodological consequences of modeling choices. The paper starts

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Marcus V?lker,Stefan Kowalewskif sophisticated, autonomous agents. The EURACE model, which has an explicit spatial structure, includes all the major markets considered in quantitative macroeconomic modelling (consumer goods, investment goods, labour, credit and finance). It offers a unique opportunity for studying, from a new per

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Marcus V?lker,Stefan Kowalewskiview of catastrophic events, like e.g. extinction events – and it is shown that these may occur at random, without external cause. Micro evolution is demonstrated looking at an actual physical problem. It turns out that there is an important distinction between natural evolution and the usage of evo

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Francesco Ranzato,Marco Zanellathese markets are organised nor as to how agents interact within them. In particular it is interesting to know how agents following rather simple rules come to coordinate. This paper discusses the modelling of these important aspects of markets and suggests that building artificial markets can compl

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Lecture Notes in Economics and Mathematical Systemshttp://image.papertrans.cn/c/image/231661.jpg

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Lecture Notes in Computer Sciencenforcement learning over a set of simple forecasting heuristics. The key element of our model is the switching between heuristics on the basis of their past performance. Simulations show that such evolutionary learning can reproduce the qualitative patterns observed in the experiment.

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