J. Gary Polhill

James Hutton Institute · Information and Computational Science

Agent-based models (ABMs) can be found across a number of diverse application areas ranging from simulating consumer behaviour to infectious disease modelling. Part of their popularity is due to their ability to simulate individual behaviours and decisions over space and time. However, whilst there are plentiful examples within the academic literat...

Even though agent-based modelling is seen as committing to a mechanistic, generative type of causation, the methodology allows for representing many other types of causal explanations. Agent-based models are capable of integrating diverse causal relationships into coherent causal mechanisms. They mirror the crucial, multi-level component of emergen...

The key message from this research, in light of lessons learned from the COVID-19 pandemic, is the need for preparation and contingency planning with national food system strategies and internationally agreed measures to protect food and nutrition security. Fundamentally, prevention, in the form of reducing climate risks through deep and rapid miti...

The report presents the results of the policy scenario workshops implemented in five clusters of social innovations: (i) Holistic, shared, and persistent mobility planning (Zürich, Switzerland and Groningen, the Netherlands); (ii) Island renaissance based on renewable energy production (Samsø, Denmark and El Hierro, Spain); (iii) Energy efficiency...

This paper discusses how data and theory were used to inform ten agent-based models in an EU Horizon 2020 project SMARTEES. The project investigates cases of social innovations implemented in different European cities, which promote low-carbon energy sources, ranging from communities insulating houses to cycling for urban transportation. The aim is...

We present results from a sensitivity analysis study of an agent-based model of district heating network adoption in an area of Aberdeen, Scotland.

Using an Agent-Based Model with a two-scale decision making process incorporating economic, geographic, social and political subsystems, we projected the rate and proportion of land use change in England and Wales from the year 2000 to the year 2050. These projections were used to assess the impact of proposals to improve arable yields, change diet...

Interdisciplinary research is especially relevant in the energy field where ambitious political targets for the energy transition require rapid advancements in technology and simultaneous developments in social norms and citizen engagement. Challenges related to interdisciplinary communication and the integration of findings across disciplines have...

Salt, DougPolhill, GaryA description of a NetLogo extension and the reasoning behind its des ign and implementation. The extension makes use of Gnu’s Pretty Good Privacy sof tware suite to encrypt arbitrary data sources in Netlogo. This both secures the data to a reasonable degree and protects any sensitive data that might be in use for a publicly...

The COVID‐19 pandemic is a major shock to society in terms of health and economy that is affecting both UK and global food and nutrition security. It is adding to the ‘perfect storm’ of threats to society from climate change, biodiversity loss and ecosystem degradation, at a time of considerable change, rising nationalism and breakdown in internati...

The acceptance and usefulness of simulation models are often limited by the efficiency, transparency, repro-ducibility, and reliability of the modelling process. We address these issues by suggesting that modellers (1) "trace" the iterative modelling process by keeping a modelling notebook corresponding to the laboratory notebooks used by empirical...

This paper addresses the highly relevant and timely issues of global trade and food security by developing an empirically grounded, relation-driven agent-based global trade model. Contrary to most price-driven trade models in the literature, the relation-driven agent-based global trade model focuses on the role of relational factors such as trust,...

This paper uses two thought experiments to argue that the complexity of the systems to which agent-based models (ABMs) are often applied is not the central source of difficulties ABMs have with prediction. We define various levels of predictability, and argue that insofar as path-dependency is a necessary attribute of a complex system, ruling out s...

Quantifying soil structural and ecological heterogeneity is crucial for understanding their interactions and their relationships to the resilience and health of the wider ecosystem. However, a clear understanding of how structural heterogeneity affects soil biodiversity is still emerging. Previous work has primarily used expensive, often laboratory...

Achieving food and nutrition security for all in a changing and globalized world remains a critical challenge of utmost importance. The development of solutions benefits from insights derived from modelling and simulating the complex interactions of the agri-food system, which range from global to household scales and transcend disciplinary boundar...

This paper accompanies the workshop on "New Tools or New Research Culture? Towards an Integration First approach to modelling social-environmental systems," and details the outcomes of a small scale workshop at The James Hutton Institute on "Modular, Integrated Agent-Based Social-Ecological Modelling." The latter workshop was predicated on the long...

Resource distribution networks are the infrastructure facilitating the flow of resources in both biotic and abiotic systems. Both theoretical and empirical arguments have proposed that physical systems self-organise to maximise power production, but how this trajectory is related to network development, especially regarding the heterogeneity of res...

The Overview, Design concepts and Details (ODD) protocol for describing Individual- and Agent-Based Models (ABMs) is now widely accepted and used to document such models in journal articles. As a standard- ized document for providing a consistent, logical and readable account of the structure and dynamics of ABMs, some research groups also find it...

The COVID-19 pandemic is causing a dramatic loss of lives worldwide, challenging the sustainability of our health care systems, threatening economic meltdown, and putting pressure on the mental health of individuals (due to social distancing and lock-down measures). The pandemic is also posing severe challenges to the scientific community, with sch...

A debt-based economy requires the accumulation of more and more debt to finance economic growth, while future economic growth is needed to repay the debt, and so the cycle continues. Despite global debt reaching unprecedented levels, little research has been done to understand the impacts of debt dynamics on environmental sustainability. Here, we e...

Agent based models (ABMs) simulate actions and interactions of autonomous agents/groups and their effect on systems as a whole, accounting for learning without assuming perfect rationality or complete knowledge. ABMs are an increasingly popular approach to studying complex, spatially distributed socio-environmental systems, but have still to become...

The activity of commuting to and from a place of work affects not only those travelling but also wider society through their contribution to congestion and pollution. It is desirable to have a means of simulating commuting in order to allow organisations to predict the effects of changes to working patterns and locations and inform decision making....

This paper develops an empirical agent-based model to assess the impacts of Brexit on Scottish cattle farms. We first identify several trends and processes among Scottish cattle farms that were ongoing before Brexit: the lack of succession, the rise of leisure farming, the trend to diversify and industrialise, and, finally, the phenomenon of the “d...

The use of agent-based modelling approaches in ex-post and ex-ante evaluations of agricultural policies has been progressively increasing over the last few years. There are now a sufficient number of models that it is worth taking stock of the way these models have been developed. Here, we review 20 agricultural agent-based models (ABM) addressing...

Socio-Ecological Systems (SESs) are the systems in which our everyday lives are embedded, so understanding them is important. The complex properties of such systems make modelling an indispensable tool for their description and analysis. Human actors play a pivotal role in SESs, but their interactions with each other and their environment are often...

This paper develops an agent-based model of global food trade based on empirical data. We investigate various social, geopolitical and economic factors that influence trade, and the impact of trade on the countries' ability to secure food for its people. The preliminary results show that global food trade has a large impact on the food security of...

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A debt-based economy cannot survive without economic growth. However, if private debt consistently grows faster than GDP, the consequences are financial crises and the current unprecedented level of global debt. This policy dilemma is aggravated by the lack of analyses factoring the impact of debt-growth cycles on the environment. What is really th...

Overview, Design Concepts and Details (ODD) Protocol. Standardized protocol describing the ABM in detail. (PDF)

Model calibration. Calibration of the ABM, based on a comparative (qualitative) analysis between Keen’s (2009, 2010a) results and our ABM results. (PDF)

Sensitivity analysis. Sensitivity analysis of the ABM, focused on analysing changes in model outputs with all parameters constant but the critical-biomass-stock parameter (for which a series of different values are considered). (PDF)

Tropical countries lie at the nexus of three pressing issues for global sustainability: agricultural production, climate change mitigation and biodiversity conservation. The forces that drive forest protection do not necessarily oppose those that drive forest clearance for development. This decoupling, enhanced by the stronger economic forces compa...

This chapter will briefly describe some common methods by which people make quantitative estimates of how well they expect empirical models to make predictions. However, the chapter’s main argument is that fit-to-data, the traditional yardstick for establishing confidence in models, is not quite the solid ground on which to build such belief some p...

The clear documentation of simulations is important for their communication, replication, and comprehension. It is thus helpful for such documentation to follow minimum standards. The ‘overview, design concepts, and details’ document protocol (ODD) is specifically designed to guide the description of individual- and agent-based simulation models (A...

Agent-based models typically have stochastic elements and many potential parameter combinations. This requires that we conduct multiple model runs to sweep the parameter space, creating large quantities of computationally generated, hyper-dimensional, “big data”. Understanding the models’ implications requires structured exploration of these comple...

In this paper we briefly expand upon Callon's Theory of Translation; a theory he elaborated with reference to the (failed) domestication of scallops by the fisherman and scientists of St. Brieuc Bay. Callon proposes a mechanism by which individual actors group together in networks that start to act as if they were a single agent. This paper details...

In this study, we develop an empirical agent-based model to investigate the mechanisms behind the decline of medium-sized cattle farms and the polarization of cattle farm size in Scotland. From local expert knowledge and existing literature, we identify three potential factors and drives of the development of cattle farms in Scotland: profitability...

This chapter reports on an exercise in replicating the analysis of outputs from 20,000 runs of a social simulation of biodiversity incentivisation (FEARLUS-SPOMM) as part of the MIRACLE project. Typically, replication refers to reconstructing the model used to generate the output from the description thereof, but for larger-scale studies, the outpu...

Rapid economic and population growth have posed challenges to Aberdeen City and Shire in UK. Some social policies can potentially be helpful to alleviate traffic congestion and help people maintain a healthy work–life balance. In this initial model, we study the impact of flexi-time work arrangement and the construction of a new bypass on average d...

This chapter compares four implementations of (Lindenberg and Steg, J Soc Issues 63(1):117–137, 2007) Goal-Framing Theory of everyday pro-environmental behaviour. Two are from different versions of CEDSS (Community Energy Demand Social Simulator, versions 3.3 and 3.4); the other two are different versions of a completely different model that also d...

Rapid economic and population growth have posed challenges to Aberdeen City and Shire in UK. Some social policies can potentially be helpful to alleviate traffic congestion and help people maintain a healthy work–life balance. In this initial model, we study the impact of flexi-time work arrangement and the construction of a new bypass on average d...

This chapter demonstrates an approach to the agent-based modelling of norm transmission using decision trees learned from questionnaire data. We explore the implications of adding norm dynamics implied in static questionnaire data and the influence social network topology has on the outcome. We find that parameters determining network topology infl...

With the increasing trend in exploring the use of agent-based models in empirical contexts, this paper reflects on the use of decision trees learned from questionnaire data as behavioral models for the agents. Decision trees are machine learning algorithms most commonly used in the data mining literature, especially for smaller datasets where other...

The CEDSS-3.4 agent-based model of domestic energy demand at community level is described. CEDSS (Community Energy Demand Social Simulator) is focused on household decisions (the model’s agents are households) to buy energy-using appliances, heating systems, and insulation, over the period from 2000 to 2049. Its empirical basis is a survey of house...

Using the O.D.D. (Overview, Design concepts, Detail) protocol, this title explores the role of agent-based modeling in predicting the feasibility of various approaches to sustainability. The chapters incorporated in this volume consist of real case studies to illustrate the utility of agent-based modeling and complexity theory in discovering a path...

Pro-environmental behaviors have been analyzed in the home, with little attention to other important contexts of everyday life, such as the workplace. The research reported here explored three categories of pro-environmental behavior (consumption of materials and energy, waste generation, and work-related commuting) in a public large-scale organiza...

The current economic crisis draws renewed attention to the underlying mechanisms of our economic system and its increasing effects on the environment. The interest rates associated with debt stocks forces society to create an increasing income flow, resulting on the accumulation of more and more debt to finance the economic growth. The impact on th...

• A participatory backcasting methodology has been developed for the GLAMURS project, entitled participatory backcasting for sustainable lifestyles and a green economy. It consists of two stakeholder workshops; a first workshop for problem exploration and development of visions for sustainable lifestyle and a green economy followed by a second work...

This paper develops an agent-based model of the daily commute in Aberdeen City and the surrounding area in Scotland, UK. We study the impact of flexitime work arrangements, urban concentration, a new bypass, and cycle lanes on commute time length, reliability and CO2 emissions, and analyse the diverse conflation of these factors and the different c...

The proliferation of agent-based models (ABMs) in recent decades has motivated model practitioners to improve the transparency, replicability, and trust in results derived from ABMs. The complexity of ABMs has risen in stride with advances in computing power and resources, resulting in larger models with complex interactions and learning and whose...

Executive summary • Agent-based models are dynamic computer simulations that explicitly represent the interactions of heterogeneous individuals. They are typically (but not always) spatially explicit, especially when simulating coupled social and natural systems. • They are well-suited to studying human-environment interactions at the local/regiona...

Agent-based modeling (ABM) is an increasingly popular technique for modeling organizations or societies. In this paper, an ABM of environmental decisions in an academic organization is devised. The decision-making model for the agents and the social network have been constructed using data obtained by responses of individuals of the organization to...

Context Habitat networks are often advocated as an effective measure for adaptation to climate change, while intensification of land use is a possible response to threats to food security. Objectives We examined the question of whether woodland networks are likely to help promote species range shift, and tried to disentangle the influence of land u...

This chapter motivates and discusses the process of making a simulation model available for others to freely inspect and use. Firstly, it outlines the three reasons why this is necessary: democratic right, scientific scrutiny, and public value extraction. Then it describes the basic steps for doing this, including: making code comprehensible, docum...

Decisions made by workers in their daily routine have an environmental impact. The LOCAW project has analyzed the drivers and barriers for an employee to choose a particular option in large organizations. In this project, Agent-Based Models (ABM) seek to clarify interactions among relevant actors and provide insights into the necessary conditions t...

One of the advantages of agent-based models as simulations of social systems is the ease with which it is possible to spatially embed the agents and their interactions. Spatially explicit representations in agent-based models most typically take the form of raster-based representations in which the space is represented as a grid of squares. More re...

This extended abstract outlines a prototype metadata standard for recording outputs of social simulations, to be refined as part of a project funded through the third round of the Digging into Data challenge. This is with a view to gathering community feedback on the proposals.

The ourSpaces Virtual Research Environment makes use of Semantic Web technologies to create a platform to support multi-disciplinary research groups. This paper introduces the main semantic components of the system: a framework to capture the provenance of the research process, a collection of services to create and visualise metadata and a policy...

The total amount of energy consumed by households over a given period of time is a function of socio-physical factors and occupant behaviour. Findings are presented here from Phase 1 of the three-phase North East Scotland Energy Monitoring Project (NESEMP), a longitudinal study of household energy consumption patterns including baseline, interventi...

A prototype of an Agent-based Model (ABM) for the LOCAW (LOw Carbon At Work) projet is presented. The main goal of LOCAW is foresight to enhance behavioral and societal changes enabling the transition towards sustainable paths in Europe. It will involve examining large employer-organizations in six different countries. This paper presents a shared...