Agent-Based Simulation for Complex Social Systems: Support for the Developer

2013 ◽  
pp. 421-425
Author(s):  
Amineh Ghorbani ◽  
Virginia Dignum
Keyword(s):  
Social Systems ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Complex Social Systems

Special Issue: Agent Based Simulation of Complex Social Systems

SIMULATION ◽  
2012 ◽  
Vol 88 (1) ◽  
pp. 4-6 ◽  
Author(s):  
Adolfo López-Paredes ◽  
Bruce Edmonds ◽  
Franziska Klugl
Keyword(s):  
Social Systems ◽  
Special Issue ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Complex Social Systems

scholarly journals Dynamic calibration of agent-based models using data assimilation

2016 ◽  
Vol 3 (4) ◽  
pp. 150703 ◽  
Author(s):  
Jonathan A. Ward ◽  
Andrew J. Evans ◽  
Nicolas S. Malleson
Keyword(s):  
Data Assimilation ◽  
Ensemble Kalman Filter ◽  
Social Systems ◽  
Open Data ◽  
Dynamical Behaviour ◽  
Agent Based Models ◽  
Agent Based ◽  
Simple Question ◽  
Complex Social Systems ◽  
Using Data

A widespread approach to investigating the dynamical behaviour of complex social systems is via agent-based models (ABMs). In this paper, we describe how such models can be dynamically calibrated using the ensemble Kalman filter (EnKF), a standard method of data assimilation. Our goal is twofold. First, we want to present the EnKF in a simple setting for the benefit of ABM practitioners who are unfamiliar with it. Second, we want to illustrate to data assimilation experts the value of using such methods in the context of ABMs of complex social systems and the new challenges these types of model present. We work towards these goals within the context of a simple question of practical value: how many people are there in Leeds (or any other major city) right now? We build a hierarchy of exemplar models that we use to demonstrate how to apply the EnKF and calibrate these using open data of footfall counts in Leeds.

Afterword: Towards a Complex Science of History

2015 ◽  
Author(s):  
Nathan Coombs
Keyword(s):  
Complexity Theory ◽  
Social Systems ◽  
Political Strategy ◽  
Agent Based ◽  
Empirical Verification ◽  
Agent Based Modelling ◽  
Science Of History ◽  
Complex Science ◽  
Complex Social Systems

This chapter begins by taking stock of the first two parts of the book. It argues that although classical Marxism cannot think events discontinuously, its science of history can at least be subjected to empirical verification. By contrast, while post-Althusserian theory succeeds in thinking events radically it does so on the basis of a self-referential rationalism that grants authority to theorists and is resistant to empirical control. To go beyond these philosophical traditions, the afterword suggests that complexity theory and ‘weak’ notions of emergence provide a way forward. Agent-based modelling of complex social systems offers a mediation of necessity and contingency that could help orient political strategy.

scholarly journals A Software Architecture for Mechanism-Based Social Systems Modelling in Agent-Based Simulation Models

2020 ◽  
Vol 23 (3) ◽  
Author(s):  
Tuong Manh Vu ◽  
Charlotte Probst ◽  
Alexandra Nielsen ◽  
Hao Bai ◽  
Petra S. Meier ◽  
...  
Keyword(s):  
Software Architecture ◽  
Social Systems ◽  
Simulation Models ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Systems Modelling

Developing Agent-Based Simulation Models for Social Systems Engineering Studies

2017 ◽  
pp. 133-156
Author(s):  
Peer-Olaf Siebers ◽  
Grazziela P. Figueredo ◽  
Miwa Hirono ◽  
Anya Skatova
Keyword(s):  
Systems Engineering ◽  
Social Systems ◽  
Simulation Models ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Engineering Studies
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