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.

Aggregation in agent-based models of economies

2012 ◽  
Vol 27 (2) ◽  
pp. 151-162 ◽  
Author(s):  
Scott E. Page
Keyword(s):  
Fixed Points ◽  
Network Structure ◽  
Social Systems ◽  
Macro Level ◽  
Agent Based Models ◽  
Agent Based ◽  
Emergent Phenomenon ◽  
Learning Rules ◽  
Equilibrium Approach ◽  
Micro Level

AbstractAgent-based models are often described as bottom-up because macro-level phenomena emerge from the micro-level interactions of agents. These macro-level phenomena include fixed points, cycles, dynamic patterns, and long transients. In this paper, I explore the link between micro-level characteristics—learning rules, diversity, network structure, and externalities—and the macro-level patterns they produce. I focus on why we need agent-level modeling, on how these models produce emergent phenomenon, and on how agent-based models help understand outcomes of social systems in a way that differs from the analytic, equilibrium approach.

Exploring Emergence within Social Systems with Agent Based Models

2014 ◽  
pp. 52-71 ◽  
Author(s):  
Marcia R. Friesen ◽  
Richard Gordon ◽  
Robert D. McLeod
Keyword(s):  
Modeling And Simulation ◽  
Real World ◽  
Research Group ◽  
Social Systems ◽  
Emergent Behavior ◽  
Agent Based Models ◽  
Social Modeling ◽  
Agent Based ◽  
Global Parameters ◽  
Representative Samples

In this chapter, the authors examine manifestations of emergence or apparent emergence in agent based social modeling and simulation, and discuss the inherent challenges in building real world models and in defining, recognizing and validating emergence within these systems. The discussion is grounded in examples of research on emergence by others, with extensions from within our research group. The works cited and built upon are explicitly chosen as representative samples of agent-based models that involve social systems, where observation of emergent behavior is a sought-after outcome. The concept of the distinctiveness of social from abiotic emergence in terms of the use of global parameters by agents is introduced.

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 Equity of Incentives: Agent-Based Explorations of How Social Networks Influence the Efficacy of Programs to Promote Solar Adoption

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Heike I. Brugger ◽  
Adam Douglas Henry
Keyword(s):  
Social Networks ◽  
Peer Effects ◽  
Social Systems ◽  
Scientific Basis ◽  
Virtual Space ◽  
Solar Pv ◽  
Agent Based Models ◽  
Agent Based ◽  
Incentive Programs ◽  
Feed In Tariff

Agent-based models are used to explore how social networks influence the effectiveness of governmental programs to promote the adoption of solar photovoltaics (solar PV) by residential households. This paper examines how a common characteristic of social networks, known as network segregation, can dampen the indirect benefits of solar incentive programs that arise from peer effects. Peer effects cause an agent to be more likely to adopt a technology if they are socially connected to other adopters. Due to network segregation, programs that target relatively affluent agents can generate rapid increases in overall adoption levels but at the cost of increasing disparities in access to solar technology between rich and poor communities. These dynamics are explored through theoretical agent-based models of solar adoption within hypothetical social systems. The effectiveness of three types of solar incentive programs, the feed-in tariff, leasing programs, and seeding programs, is explored. Even though these programs promote rapid adoption in the short term, results demonstrate that network segregation can create serious distributional justice problems in the long term for some programs. The distributional justice effects are particularly severe with the feed-in tariff. Overall, this paper provides an illustration of how agent-based models may be used to evaluate and experiment with policy interventions in a virtual space, which enhances the scientific basis of policymaking.

scholarly journals Intra-group decision-making in agent-based models

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Allegra A. Beal Cohen ◽  
Rachata Muneepeerakul ◽  
Gregory Kiker
Keyword(s):  
Decision Making ◽  
Functional Groups ◽  
Group Dynamics ◽  
Group Decision Making ◽  
Local Governments ◽  
Large Scale ◽  
Group Decision ◽  
Social Systems ◽  
Agent Based Models ◽  
Agent Based

AbstractMany agent-based models (ABMs) try to explain large-scale phenomena by reducing them to behaviors at lower scales. At these scales in social systems are functional groups such as households, religious congregations, coops and local governments. The intra-group dynamics of functional groups often generate inefficient or unexpected behavior that cannot be predicted by modeling groups as basic units. We introduce a framework for modeling intra-group decision-making and its interaction with social norms, using the household as our focus. We select phenomena related to women’s empowerment in agriculture as examples influenced by both intra-household dynamics and gender norms. Our framework proves more capable of replicating these phenomena than two common types of ABMs. We conclude that it is not enough to build multi-scale models; explaining social behaviors entails modeling intra-scale dynamics.

Sign in / Sign up

Export Citation Format

Share Document