Using Agent-Based Models for Prediction in Complex and Wicked Systems

J. Gareth Polhill (), Matthew Hare (), Tom Bauermann (), David Anzola (), Erika Palmer (), Doug Salt () and Patrycja Antosz ()
Additional contact information
J. Gareth Polhill: https://www.hutton.ac.uk/people/gary-polhill/
Matthew Hare: https://www.hutton.ac.uk/staff/matt-hare
Tom Bauermann: https://www.ruhr-uni-bochum.de/mak/team/bauermann.html.en
Erika Palmer: https://ruralis.no/en/employees/erikapalmer/
Doug Salt: https://www.hutton.ac.uk/staff/doug-salt

Journal of Artificial Societies and Social Simulation, 2021, vol. 24, issue 3, 2

Abstract: 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 states of the system means that there is at least the potential to say something useful. ‘Wickedness’ is argued to be a more significant challenge to prediction than complexity. Critically, however, neither complexity nor wickedness makes prediction theoretically impossible in the sense of being formally undecidable computationally-speaking: intractable being the more apt term given the exponential sizes of the spaces being searched. However, endogenous ontological novelty in wicked systems is shown to render prediction futile beyond the immediately short term.

Keywords: Prediction; Complex Systems; Wicked Systems; Agent-Based Modelling; Cellular Automata; Turing Machines (search for similar items in EconPapers)
Date: 2021-06-30
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.jasss.org/24/3/2/2.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:jas:jasssj:2020-137-4

Access Statistics for this article

More articles in Journal of Artificial Societies and Social Simulation from Journal of Artificial Societies and Social Simulation
Bibliographic data for series maintained by Francesco Renzini ().