Heppenstall, A orcid.org/0000-0002-0663-3437 and Malleson, N orcid.org/0000-0002-6977-0615 (2020) Building cities from slime mould, agents and quantum field theory. In: Proc. of the 19th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2020). 19th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2020), 09-13 May 2020, Online. ISBN 978-1-4503-7518-4
Abstract
Managing the unprecedented growth of cities whilst ensuring that they are sustainable, healthy and equitable places to live, presents significant challenges. Our current thinking conceptualise cities as being driven by processes from the bottom-up, with an emphasis on the role that individual decisions and behaviour play. Multiagent systems, and agent-based modelling in particular, are ideal frameworks for the analysis of such systems. However, identifying the important drivers within an urban system, translating key behaviours from data into rules, quantifying uncertainty and running models in real time all present significant challenges. We discuss how innovations in a diverse range of fields are influencing empirical agent-based models, and how models designed for the simplest biological systems might transform the ways that we understand and manage real cities.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved. This is an author produced version of a conference paper published in Proceedings of AAMAS'20. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | agent-based modelling; urban analytics; slime mould; data assimilation; quantum field theory; uncertainty; behaviour |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Geography (Leeds) > Centre for Spatial Analysis & Policy (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 12 May 2020 08:30 |
Last Modified: | 28 Jul 2020 14:41 |
Status: | Published |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:159618 |