Learning and imitation: Transitional dynamics in variants of the BAM

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We study the dynamics of self-organized systems when disturbed by shocks. For this purpose, we consider extensions of the "Bar Attendance Model" [1] (BAM), which provides a stylized setting for the analysis of the emergence of coordination in the behavior of a large collection of agents. W...

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Detalles Bibliográficos
Autores principales:	Heymann, D., Perazzo, R.P.J., Schuschny, A.R.
Formato:	JOUR
Materias:	Contagion effects Coordination problems Genetic algorithms Multi-agent models Self-organization Transitional dynamics Information analysis Mathematical models Multi agent systems Problem solving Self organizing maps Learning systems
Acceso en línea:	http://hdl.handle.net/20.500.12110/paper_02195259_v7_n1_p21_Heymann
Aporte de:	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires

id	todo:paper_02195259_v7_n1_p21_Heymann
record_format	dspace
spelling	todo:paper_02195259_v7_n1_p21_Heymann2023-10-03T15:11:08Z Learning and imitation: Transitional dynamics in variants of the BAM Heymann, D. Perazzo, R.P.J. Schuschny, A.R. Contagion effects Coordination problems Genetic algorithms Multi-agent models Self-organization Transitional dynamics Genetic algorithms Information analysis Mathematical models Multi agent systems Problem solving Self organizing maps Contagion effects Coordination problems Multi-agent models Self-organization Transitional dynamics Learning systems We study the dynamics of self-organized systems when disturbed by shocks. For this purpose, we consider extensions of the "Bar Attendance Model" [1] (BAM), which provides a stylized setting for the analysis of the emergence of coordination in the behavior of a large collection of agents. We represent the learning process of the agents through genetic algorithms, which respond to global (publicly available) information. In addition, we allow the actions of agents to be influenced by local information, as expressed in the behavior and performance of neighboring individuals. In the context of the BAM, we show that, in the event of a shock, the imitation behavior may become widespread and generate a contagion cascade which mimics a collective panic. We use this framework to represent features of the dynamics of an actual bank run. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_02195259_v7_n1_p21_Heymann
institution	Universidad de Buenos Aires
institution_str	I-28
repository_str	R-134
collection	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic	Contagion effects Coordination problems Genetic algorithms Multi-agent models Self-organization Transitional dynamics Genetic algorithms Information analysis Mathematical models Multi agent systems Problem solving Self organizing maps Contagion effects Coordination problems Multi-agent models Self-organization Transitional dynamics Learning systems
spellingShingle	Contagion effects Coordination problems Genetic algorithms Multi-agent models Self-organization Transitional dynamics Genetic algorithms Information analysis Mathematical models Multi agent systems Problem solving Self organizing maps Contagion effects Coordination problems Multi-agent models Self-organization Transitional dynamics Learning systems Heymann, D. Perazzo, R.P.J. Schuschny, A.R. Learning and imitation: Transitional dynamics in variants of the BAM
topic_facet	Contagion effects Coordination problems Genetic algorithms Multi-agent models Self-organization Transitional dynamics Genetic algorithms Information analysis Mathematical models Multi agent systems Problem solving Self organizing maps Contagion effects Coordination problems Multi-agent models Self-organization Transitional dynamics Learning systems
description	We study the dynamics of self-organized systems when disturbed by shocks. For this purpose, we consider extensions of the "Bar Attendance Model" [1] (BAM), which provides a stylized setting for the analysis of the emergence of coordination in the behavior of a large collection of agents. We represent the learning process of the agents through genetic algorithms, which respond to global (publicly available) information. In addition, we allow the actions of agents to be influenced by local information, as expressed in the behavior and performance of neighboring individuals. In the context of the BAM, we show that, in the event of a shock, the imitation behavior may become widespread and generate a contagion cascade which mimics a collective panic. We use this framework to represent features of the dynamics of an actual bank run.
format	JOUR
author	Heymann, D. Perazzo, R.P.J. Schuschny, A.R.
author_facet	Heymann, D. Perazzo, R.P.J. Schuschny, A.R.
author_sort	Heymann, D.
title	Learning and imitation: Transitional dynamics in variants of the BAM
title_short	Learning and imitation: Transitional dynamics in variants of the BAM
title_full	Learning and imitation: Transitional dynamics in variants of the BAM
title_fullStr	Learning and imitation: Transitional dynamics in variants of the BAM
title_full_unstemmed	Learning and imitation: Transitional dynamics in variants of the BAM
title_sort	learning and imitation: transitional dynamics in variants of the bam
url	http://hdl.handle.net/20.500.12110/paper_02195259_v7_n1_p21_Heymann
work_keys_str_mv	AT heymannd learningandimitationtransitionaldynamicsinvariantsofthebam AT perazzorpj learningandimitationtransitionaldynamicsinvariantsofthebam AT schuschnyar learningandimitationtransitionaldynamicsinvariantsofthebam
_version_	1782025498093682688

Learning and imitation: Transitional dynamics in variants of the BAM

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