By Riccardo Boero; Matteo Morini; Michele Sonnessa; Pietro Terna
This publication objective is twofold. First, it introduces the reader to the method and to the technicalities and the instruments essential to grasp the construction of agent-based versions. moment, it offers numerous examples of functions to diverse monetary phenomena the place agent-based versions are the most important in answering the examine query and in fixing sensible difficulties emerged in enterprise and coverage domain names (e.g., monetary markets, cooperation dynamics, public coverage evaluation).
With this ebook, readers examine what agent-based types are and the benefits they could offer. additional, readers how you can enhance from scratch and with medical rigor their very own agent-based versions for learning fiscal phenomena. ultimately, readers locate within the publication numerous functions which can characterize examples to be imitated and to be saved as reference.
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Extra info for Agent-based Models of the Economy: From Theories to Applications
Computer simulation can combine the useful flexibility of a computer code – where we can create agents acting, making choices, and reacting to the choices of other agents and to modification of their environment – and its intrinsic computability. In this way we can combine the descriptive capabilities of verbal argumentation and the ability to calculate the effects of different situations and hypotheses. From this perspective, the computer program is a form of mathematics. In addition, we can generate data – that is, time series – from our models and analyze them employing statistics and econometrics.
2, when science already applies (ii) to describe, explain, and forecast reality, which is, per se, too complicated to be understood? In reply we can first, by using ABMs and simulation, produce artifacts of actual systems, and play with them. In this way, we can discover the consequences both of well-known ex-ante hypotheses and of agents’ behavioral designs and interaction structures. Then we can apply statistics and econometrics to the outcomes of the simulations, and compare the results with those obtained by applying the same tests to actual data.
M. , Generative Social Science: Studies in Agent-based Computational Modeling. Princeton University Press, Princeton, NJ, p. 146. Diallo, S. , Padilla, J. , Herencia-Zapana, H. and Tolk, A. (2013). Toward a Formalism of Modeling and Simulation using Model Theory. Complexity, pp. 56–63. 21478. Epstein, J. and Axtell, R. (1994). Agent-based Modeling: Understanding Our Creations. The Bulletin of The Santa Fe Institute (Winter), pp. 28–32. Gilbert, N. and Terna, P. (2000). How To Build and Use Agent-based Models in Social Science.