Sascha Hokamp, Ph D is a member of the Research Unit for Sustainability and Global Change (FNU) and of the Center for Earth System Research and Sustainability (CEN), Universität Hamburg. His research topics include illicit activities (tax evasion and doping in elite sports) and the shadow economy.
László Gulyás, Ph D is Assistant Professor at Eötvös Loránd University, Budapest. He is a former Head of Division at AITIA International, Inc. He has been doing research on agent-based modeling and multi-agent systems since 1996.
Matthew Koehler, Ph D is the Applied Complexity Sciences Area Lead for US Treasury/Internal Revenue Service, US Commerce, and Social Security Administration Program Division at The MITRE Corporation.
Sanith Wijesinghe, Ph D is Chief Engineer of the Model Based Analytics department at The MITRE Corporation.
4 Ebook di Laszlo Gulyas
Sascha Hokamp & Laszlo Gulyas: Agent-based Modeling of Tax Evasion
The only single-source guide to understanding, using, adapting, and designing state-of-the-art agent-based modelling of tax evasion A computational method for simulating the behavior of individuals o …
PDF
Inglese
DRM
€75.99
Sascha Hokamp & Laszlo Gulyas: Agent-based Modeling of Tax Evasion
The only single-source guide to understanding, using, adapting, and designing state-of-the-art agent-based modelling of tax evasion A computational method for simulating the behavior of individuals o …
EPUB
Inglese
DRM
€75.99
Janos Botzheim & Laszlo Gulyas: Computational Collective Intelligence
This book constitutes the refereed proceedings of the 15th International Conference on Computational Collective Intelligence, ICCCI 2023, held in Budapest, Hungary, during September 27-29, 2023.The 6 …
EPUB
Inglese
DRM
€114.69
Janos Botzheim & Laszlo Gulyas: Advances in Computational Collective Intelligence
This book constitutes the refereed proceedings of the 15th International Conference on Advances in Computational Collective Intelligence, ICCCI 2023, held in Budapest, Hungary, during September 27-29 …
EPUB
Inglese
DRM
€127.42