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Titel
Deep learning in agent-based models : a prospectus / Sander van der Hoog
VerfasserHoog, Sander van der
ErschienenBielefeld, Germany : Universität Bielefeld, Faculty of Business Administration and Economics, January 2016
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Elektronische Ressource
Umfang1 Online-Ressource (18 Seiten) : 1 Illustration
SerieWorking papers in economics and management ; No. 02-2016
URNurn:nbn:de:hbz:6:2-127504 
DOI10.4119/unibi/2900219 
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Deep learning in agent-based models [0.26 mb]
Zusammenfassung

A very timely issue for economic agent-based models (ABMs) is their empirical estimation. This paper describes a line of research that could resolve the issue by using machine learning techniques, using multi-layer artificial neural networks (ANNs), or so called Deep Nets. The seminal contribution by Hinton et al. (2006) introduced a fast and efficient training algorithm called Deep Learning, and there have been major breakthroughs in machine learning ever since. Economics has not yet benefited from these developments, and therefore we believe that now is the right time to apply Deep Learning and multi-layered neural networks to agent-based models in economics.

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