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BEGIN:VEVENT
DTSTAMP:20260502T143145Z
DTSTART;VALUE=DATE-TIME:20240313T143000
DTEND;VALUE=DATE-TIME:20240313T153000
SUMMARY:Talk by Kavin Narasimhan\, CIM -- "Agent-based Modelling in Gover
 nment"
TZID:Europe/London
UID:20240313-8a1785d78d5a927b018d6516906a461e@warwick.ac.uk
CREATED:20240312T114957Z
DESCRIPTION:Agent-based Modelling in Government Kavin Narasimhan Agent-ba
 sed Modelling (ABM) is a bottom-up approach used to replicate the behavi
 our of complex systems\, like societies\, in silico by simulating the be
 haviour of individual units called agents\, which represent entities lik
 e people\, businesses\, and policymakers. The interactions between agent
 s and their environment result in macro-level patterns or outcomes that 
 are computationally irreducible and hard to describe using mathematical 
 equations for reasons including agent heterogeneity\, adaptive behaviour
 s\, nonlinearity\, and path dependence. ABM captures these characteristi
 cs effectively to simulate the emergence of complex phenomena from micro
 -level assumptions and is easy to implement with the availability of rig
 ht data. However\, its concepts are challenging to master\, and there ar
 e limitations. Building a model at the right level of description with t
 he right amount of detail requires resources and interdisciplinary exper
 tise\; the results obtained from simulating human behaviour can range fr
 om being purely qualitative to highly quantitative and thus require huma
 n expertise to interpret the results to generate insights\; validating t
 he macro-level patterns and micro-level assumptions in ABM requires fine
 -grained data\; and finally\, ABM is computationally expensive. Against 
 the backdrop of the challenges and opportunities of ABM\, our research s
 eeks to explore the application of ABM in Government by foregrounding th
 e practical experiences of modellers and model users in using ABM to aid
  planning and decision-making. Kavin will present emerging findings base
 d on interviews conducted with agent-based modellers and model users for
 /in Government. There will be opportunities to hear about and reflect on
  the use of ABM and other bottom-up modelling approaches to capture hete
 rogeneity\, the relevance of models at specific stages of the policy cyc
 le\, the collaborative relationship between model developers and model u
 sers and its consequences for model application and legacy\, issues of u
 ncertainty in bottom-up modelling\, and implications for quality assuran
 ce. Speaker bio: Dr Kavin Narasimhan is an Assistant Professor at the Ce
 ntre for Interdisciplinary Methodologies (CIM) at the University of Warw
 ick. Her research focuses on computational modelling for public policy u
 sing methods like agent-based modelling\, causal loop diagramming\, netw
 ork mapping and analysis. She is also interested in knowledge co-product
 ion using participatory research methods. Kavin's work reviewing the use
  of ABM in Government was supported by the UK Research and Innovation (U
 KRI) Economic and Social Research Council (ESRC) as part of the Policy F
 ellowships pilot programme [ES/W008548/1].
LOCATION:S2.77
CATEGORIES:
LAST-MODIFIED:20240312T114957Z
ORGANIZER;CN=Erica Kendrick:
END:VEVENT
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