384 research outputs found

    ODD Updated

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    An update to Volker Grimm and colleagues\' Overview, Design concepts and Details (ODD) protocol for documenting individual and agent based models (I/ABM) has recently been published in Ecological Modelling. This renames the \'State variables and scales\' element to \'Entities, state variables and scales\', and the \'Input\' element to \'Input data\', introduces two new Design concepts (\'Basic principles\' and \'Learning\'), and renames another (\'Fitness\' is now generalised to \'Objectives\'). The Design concepts element can now also be shortened such that it is not required to include any design concept that is irrelevant to the model, and expanded to include new design concepts more appropriate to the model being described. Other clarifications of intentions in the original protocol have been made.ODD, Individual Based Models, Agent Based Models, Replication, Documentation

    Is Your Model Susceptible to Floating-Point Errors?

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    This paper provides a framework that highlights the features of computer models that make them especially vulnerable to floating-point errors, and suggests ways in which the impact of such errors can be mitigated. We focus on small floating-point errors because these are most likely to occur, whilst still potentially having a major influence on the outcome of the model. The significance of small floating-point errors in computer models can often be reduced by applying a range of different techniques to different parts of the code. Which technique is most appropriate depends on the specifics of the particular numerical situation under investigation. We illustrate the framework by applying it to six example agent-based models in the literature.Floating Point Arithmetic, Floating Point Errors, Agent Based Modelling, Computer Modelling, Replication

    Using Qualitative Evidence to Enhance an Agent-Based Modelling System for Studying Land Use Change

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    This paper describes and evaluates a process of using qualitative field research data to extend the pre-existing FEARLUS agent-based modelling system through enriching its ontological capabilities, but without a deep level of involvement of the stakeholders in designing the model itself. Use of qualitative research in agent-based models typically involves protracted and expensive interaction with stakeholders; consequently gathering the valuable insights that qualitative methods could provide is not always feasible. At the same time, many researchers advocate building completely new models for each scenario to be studied, violating one of the supposed advantages of the object-oriented programming languages in which many such systems are built: that of code reuse. The process described here uses coded interviews to identify themes suggesting changes to an existing model, the assumptions behind which are then checked with respondents. We find this increases the confidence with which the extended model can be applied to the case study, with a relatively small commitment required on the part of respondents.Agent-Based Modelling, Land Use/Cover Change, Qualitative Research, Interdisciplinary Research

    Semantic Support for Computational Land-Use Modelling

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    Postprin

    A Semantic Workflow Mechanism to Realize Experimental Goals and Constraints

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    Postprin

    The CEDSS model of direct domestic energy demand

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    This paper describes the design, implementation and testing of the CEDSS model of direct domestic energy demand, and the first results of its use to produce estimates of future demand under a range of scenarios. CEDSS simulates direct domestic energy demand at within communities of approximately 200 households. The scenarios explored differ in the economic conditions assumed, and policy measures adopted at national level

    A Semantic Grid Service for Experimentation with an Agent-Based Model of Land-Use Change

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    Agent-based models, perhaps more than other models, feature large numbers of parameters and potentially generate vast quantities of results data. This paper shows through the FEARLUS-G project (an ESRC e-Social Science Initiative Pilot Demonstrator Project) how deploying an agent-based model on the Semantic Grid facilitates international collaboration on investigations using such a model, and contributes to establishing rigorous working practices with agent-based models as part of good science in social simulation. The experimental workflow is described explicitly using an ontology, and a Semantic Grid service with a web interface implements the workflow. Users are able to compare their parameter settings and results, and relate their work with the model to wider scientific debate.Agent-Based Social Simulation, Experiments, Ontologies, Replication, Semantic Grid

    When and How to Imitate Your Neighbours: Lessons from and for FEARLUS

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    This paper summarises some previously published work on imitation, experimentation (or innovation) and aspiration thresholds using the FEARLUS modelling system and reports new work with FEARLUS extending these studies. Results are discussed in the context of existing literature on imitation and innovation in related contexts. A form of imitation in which land uses are selected on the criterion of their recent performance within the neighbourhood of the land parcel concerned (called here 'Best-mean Imitation'), outperforms comparably simple forms of imitation in a wide range of FEARLUS Environments. However, the choice of criterion is shown to interact with both the way the criterion is applied, and the land manager's aspiration threshold: the level of return with which they are satisfied. The implications of work with FEARLUS for the broader bodies of research discussed, and vice versa, are considered.Imitation, Innovation, Aspiration, Land-Use, Spatio-Temporal Heterogeneity

    It's not the 'what', but the 'how':Exploring the role of debt in natural resource (un)sustainability

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    <div><p>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 the relationship between debt and natural resource sustainability, and what is the role of debt in decoupling economic growth from natural resource availability? Here we present a conceptual Agent-Based Model (ABM) that integrates an environmental system into an ABM representation of Steve Keenā€™s debt-based economic models. Our model explores the extent to which debt-driven processes, within debt-based economies, enhance the decoupling between economic growth and the availability of natural resources. Interestingly, environmental and economic collapse in our model are not caused by debt growth, or the debt-based nature of the economic system itself (i.e. the ā€˜<i>what</i>ā€™), but rather, these are due to the inappropriate use of debt by private actors (i.e. the ā€˜<i>how</i>ā€™). Firms inappropriately use bank credits for speculative goalsā€“rather than production-oriented onesā€“and for exponentially increasing rates of technological development. This context creates temporal mismatches between natural resource growth and firmsā€™ resource extraction rates, as well as between economic growth and the capacity of the government to effectively implement natural resource conservation policies. This paper discusses the extent to which economic growth and the availability of natural resources can be re-coupled through a more sustainable use of debt, for instance by shifting mainstream banking forces to partially support environmental conservation as well as economic growth.</p></div
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