Pure functional epidemics

Thaler, Jonathan; Altenkirch, Thorsten; Siebers, Peer-Olaf

Abstract

Agent-Based Simulation (ABS) is a methodology in which a system is simulated in a bottom-up approach by modelling the micro interactions of its constituting parts, called agents, out of which the global system behaviour emerges. So far mainly object-oriented techniques and languages have been used in ABS. Using the SIR model of epidemiology, which simulates the spreading of an infectious disease through a population, we demonstrate how to use pure Functional Reactive Programming to implement ABS. With our approach we can guarantee the reproducibility of the simulation at compile time and rule out specific classes of run-time bugs, something that is not possible with traditional object-oriented languages. Also, we found that the representation in a purely functional format is conceptually quite elegant and opens the way to formally reason about ABS.

Citation

Thaler, J., Altenkirch, T., & Siebers, P. (2018). Pure functional epidemics. In IFL'18 Proceedings of 30th Symposium on Implementation and Application of Functional Languages, 5-7 September 2018, Lowell, Mass., USA, 1-12. doi:10.1145/3310232.3310372

• Conference Name: 30th Symposium on Implementation and Application of Functional Languages
• Start Date: Sep 5, 2018
• End Date: Sep 7, 2018
• Acceptance Date: Jul 24, 2018
• Online Publication Date: Sep 5, 2018
• Publication Date: Sep 5, 2018
• Deposit Date: Aug 21, 2018
• Publicly Available Date: Oct 6, 2018
• Publisher: Association for Computing Machinery (ACM)
• Pages: 1-12
• Book Title: IFL'18 Proceedings of 30th Symposium on Implementation and Application of Functional Languages, 5-7 September 2018, Lowell, Mass., USA
• Chapter Number: n/a
• ISBN: 978-1-4503-7143-8
• DOI: https://doi.org/10.1145/3310232.3310372
• Keywords: Functional Reactive Programming, Monadic Stream Functions, Agent- Based Simulation
• Public URL: https://nottingham-repository.worktribe.com/output/1041336
• Publisher URL: https://dl.acm.org/citation.cfm?id=3310372
• Additional Information: Conference website: http://2018.iflconference.org/; ; ACM digital library: https://dl.acm.org/