TY  - GEN
AB  - 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.
DA  - 2016
DO  - 10.4119/unibi/2900219
KW  - Deep Learning
KW  - Agent-Based Models
KW  - Estimation
KW  - Meta-modelling
KW  - etace_agent_based_modelling
KW  - etace_WP
LA  - eng
PY  - 2016
SN  - 2196-2723
SP  - 19-
TI  - Deep Learning in Agent-Based Models: A Prospectus
UR  - https://nbn-resolving.org/urn:nbn:de:0070-pub-29002192
Y2  - 2024-11-22T04:01:16
ER  -