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

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.

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Endogenous Social Networks from Large-Scale Agent-Based Models

2017 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW) ◽

10.1109/ipdpsw.2017.83 ◽

2017 ◽

Author(s):

Eric Tatara ◽

Nicholson Collier ◽

Jonathan Ozik ◽

Charles Macal

Keyword(s):

Social Networks ◽

Large Scale ◽

Agent Based Models ◽

Agent Based

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Using Quantum Agent-Based Simulation to Model Social Networks

Semantic Web Personalization and Context Awareness ◽

10.4018/978-1-61520-921-7.ch005 ◽

2011 ◽

pp. 42-54

Author(s):

C. Bisconti ◽

A. Corallo ◽

M. De Maggio ◽

F. Grippa ◽

S. Totaro

Keyword(s):

Social Networks ◽

Quantum Mechanics ◽

Quantum Physics ◽

Business Processes ◽

Social Dynamics ◽

Social Systems ◽

Many Body ◽

Agent Based ◽

Microscopic Interactions ◽

The Many

This research aims to apply models extracted from the many-body quantum mechanics to describe social dynamics. It is intended to draw macroscopic characteristics of organizational communities starting from the analysis of microscopic interactions with respect to the node model. In this chapter, the authors intend to give an answer to the following question: which models of the quantum physics are suitable to represent the behaviour and the evolution of business processes? The innovative aspects of the project are related to the application of models and methods of the quantum mechanics to social systems. In order to validate the proposed mathematical model, the authors intend to define an open-source platform able to model nodes and interactions within a network, to visualize the macroscopic results through a digital representation of the social networks.

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Dynamic calibration of agent-based models using data assimilation

Royal Society Open Science ◽

10.1098/rsos.150703 ◽

2016 ◽

Vol 3 (4) ◽

pp. 150703 ◽

Cited By ~ 22

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.

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Aggregation in agent-based models of economies

The Knowledge Engineering Review ◽

10.1017/s0269888912000112 ◽

2012 ◽

Vol 27 (2) ◽

pp. 151-162 ◽

Cited By ~ 17

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.

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A Theoretical Framework for Conducting Multi-Level Studies of Complex Social Systems With Agent-Based Models and Empirical Data

SSRN Electronic Journal ◽

10.2139/ssrn.2280789 ◽

2011 ◽

Author(s):

Chih-Chun Chen

Keyword(s):

Empirical Data ◽

Social Systems ◽

Theoretical Framework ◽

Agent Based Models ◽

Agent Based ◽

Multi Level ◽

Complex Social Systems

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Exploring Emergence within Social Systems with Agent Based Models

Interdisciplinary Applications of Agent-Based Social Simulation and Modeling - Advances in Human and Social Aspects of Technology ◽

10.4018/978-1-4666-5954-4.ch004 ◽

2014 ◽

pp. 52-71 ◽

Cited By ~ 2

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.

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Intra-group decision-making in agent-based models

Scientific Reports ◽

10.1038/s41598-021-96661-5 ◽

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.

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Statistical analysis of tipping pathways in agent-based models

The European Physical Journal Special Topics ◽

10.1140/epjs/s11734-021-00191-0 ◽

2021 ◽

Author(s):

Luzie Helfmann ◽

Jobst Heitzig ◽

Péter Koltai ◽

Jürgen Kurths ◽

Christof Schütte

Keyword(s):

Social Systems ◽

Large Population ◽

Dimensional Structure ◽

Agent Based Models ◽

Agent Based ◽

Cascading Effects ◽

Majority Opinion ◽

Transition Path Theory ◽

Natural Choice ◽

Low Dimensional

AbstractAgent-based models are a natural choice for modeling complex social systems. In such models simple stochastic interaction rules for a large population of individuals on the microscopic scale can lead to emergent dynamics on the macroscopic scale, for instance a sudden shift of majority opinion or behavior. Here we are introducing a methodology for studying noise-induced tipping between relevant subsets of the agent state space representing characteristic configurations. Due to a large number of interacting individuals, agent-based models are high-dimensional, though usually a lower-dimensional structure of the emerging collective behaviour exists. We therefore apply Diffusion Maps, a non-linear dimension reduction technique, to reveal the intrinsic low-dimensional structure. We characterize the tipping behaviour by means of Transition Path Theory, which helps gaining a statistical understanding of the tipping paths such as their distribution, flux and rate. By systematically studying two agent-based models that exhibit a multitude of tipping pathways and cascading effects, we illustrate the practicability of our approach.

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