Special Issue "Innovations in Agent-Based Modelling of Spatial Systems"

A special issue of ISPRS International Journal of Geo-Information (ISSN 2220-9964).

Deadline for manuscript submissions: closed (20 December 2020).

Special Issue Editors

Prof. Dr. Nick Malleson
E-Mail Website
Guest Editor
School of Geography, University of Leeds, Leeds, LS2 9JT, UK
Interests: agent-based modelling; social simulation; geographical information science; urban analytics; crime modelling; machine learning
Prof. Dr. Ed Manley
E-Mail Website
Guest Editor
School of Geography, University of Leeds, Leeds, LS2 9JT, UK
Interests: agent-based modelling; machine learning; route choice; urban analytics; traffic simulation
Special Issues and Collections in MDPI journals
Prof. Dr. Alison Heppenstall
E-Mail Website
Guest Editor
School of Geography, University of Leeds, Leeds, LS2 9JT, UK
Interests: individual-based modelling; urban analytics; behavioural modelling; uncertainty quantification

Special Issue Information

Dear Colleagues,

Agent-Based Modelling is a method that is ideally suited to modelling many social and spatial phenomena, particularly in human-environmental systems where the interactions and behaviours of heterogeneous individuals are key to understanding the wider system-level behaviour. Although it is a relatively new method that understandably receives criticism, significant progress has been made towards: (i) strengthening the reliability of agent-based models through the development of comprehensive validation methods; (ii) the use of new data sources to better capture observed and simulated patterns at different scales; or  (iii) through closer working with the ‘end users’ of research, such as policy makers and businesses, so that the uncertainties and limitations of any modelled results are properly understood.

This Special Issue aims to capture state-of-the-art findings in agent-based modelling of spatial systems, with a particular emphasis on papers that are advancing the discipline through new approaches to validation, the use of new data, or policy-focussed work that can evidence a strong collaboration with end users. We encourage papers ranging from those that address fundamental methodological issues in toy systems to fully-fledged empirical applications. Submissions are particularly encouraged from early-career researchers, following the European Research Council definition of within 7 years since the completion of their PhD (plus additional allowances for career breaks etc.). Research supervisors and senior colleagues are allowed as co-authors, but the lead author must be an early career researcher.

 
Submissions are invited that cover a range of issues, with topics including (but not limited to):

  • Methods to support better validation of spatial agent-based models
  • Empirical applications of spatial agent-based models
  • The use of innovative methods to advance agent-based modelling, such as machine learning, AI methods, or Bayesian approaches
  • The incorporation of novel data to inform agent-based models, such as volunteered geographical information or ‘big’ data sources
  • Modelling spatial systems in real time
  • Understanding and/or quantifying the uncertainty associated with spatial agent-based models
  • Applications of agent-based modelling to policy-focussed problems
  • Developments in the visualisation of spatial agent-based models
  • Applications focussed on urban phenomena such as short-term population flows, crowding/congestion, pollution, etc.


Prof. Dr. Nick Malleson
Prof. Dr. Ed Manley
Prof. Dr. Alison Heppenstall
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. ISPRS International Journal of Geo-Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Agent-Based Modelling
  • Spatial Systems
  • Geographical Information Science
  • GIS
  • Multi-Agent Simulation
  • Early Career
  • Urban Analytics

Published Papers (2 papers)

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Research

Open AccessArticle
Beyond Objects in Space-Time: Towards a Movement Analysis Framework with ‘How’ and ‘Why’ Elements
ISPRS Int. J. Geo-Inf. 2021, 10(3), 190; https://doi.org/10.3390/ijgi10030190 - 22 Mar 2021
Viewed by 332
Abstract
Current spatiotemporal data has facilitated movement studies to shift objectives from descriptive models to explanations of the underlying causes of movement. From both a practical and theoretical standpoint, progress in developing approaches for these explanations should be founded on a conceptual model. This [...] Read more.
Current spatiotemporal data has facilitated movement studies to shift objectives from descriptive models to explanations of the underlying causes of movement. From both a practical and theoretical standpoint, progress in developing approaches for these explanations should be founded on a conceptual model. This paper presents such a model in which three conceptual levels of abstraction are proposed to frame an agent-based representation of movement decision-making processes: ‘attribute,’ ‘actor,’ and ‘autonomous agent’. These in combination with three temporal, spatial, and spatiotemporal general forms of observations distinguish nine (3 × 3) representation typologies of movement data within the agent framework. Thirdly, there are three levels of cognitive reasoning: ‘association,’ ‘intervention,’ and ‘counterfactual’. This makes for 27 possible types of operation embedded in a conceptual cube with the level of abstraction, type of observation, and degree of cognitive reasoning forming the three axes. The conceptual model is an arena where movement queries and the statement of relevant objectives takes place. An example implementation of a tightly constrained spatiotemporal scenario to ground the agent-structure was summarised. The platform has been well-defined so as to accommodate different tools and techniques to drive causal inference in computational movement analysis as an immediate future step. Full article
(This article belongs to the Special Issue Innovations in Agent-Based Modelling of Spatial Systems)
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Open AccessArticle
An Empirical Agent-Based Model for Regional Knowledge Creation in Europe
ISPRS Int. J. Geo-Inf. 2020, 9(8), 477; https://doi.org/10.3390/ijgi9080477 - 30 Jul 2020
Viewed by 621
Abstract
Modelling the complex nature of regional knowledge creation is high on the research agenda. It deals with the identification of drivers for regional knowledge creation of different kinds, among them inter-regional networks and agglomeration factors, as well as their interplay; i.e., in which [...] Read more.
Modelling the complex nature of regional knowledge creation is high on the research agenda. It deals with the identification of drivers for regional knowledge creation of different kinds, among them inter-regional networks and agglomeration factors, as well as their interplay; i.e., in which way they influence regional knowledge creation and accordingly, innovation capabilities—in the short- and long-term. Complementing a long line of tradition—establishing a link between regional knowledge input indicators and knowledge output in a regression framework—we propose an empirically founded agent-based simulation model that intends to approximate the complex nature of the multi-regional knowledge creation process for European regions. Specifically, we account for region-internal characteristics, and a specific embedding in the system of region-internal and region-external R&D collaboration linkages. With first exemplary applications, we demonstrate the potential of the model in terms of its robustness and empirical closeness. The model enables the replication of phenomena and current scientific issues of interest in the field of geography of innovation and hence, shows its potential to advance the scientific debate in this field in the future. Full article
(This article belongs to the Special Issue Innovations in Agent-Based Modelling of Spatial Systems)
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