Fluid approximation based analysis for mode-switching population dynamics

Paul Piho, Jane Hillston

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

Fluid approximation results provide powerful methods for scalable analysis of models of population dynamics with large numbers of discrete states and have seen wide ranging applications in modelling biological and computer-based systems and model checking. However the applicability of these methods relies on assumptions that are not easily met in a number of modelling scenarios. This paper focuses on one particular class of scenarios in which rapid information propagation in the system is considered. In particular, we study the case where changes in population dynamics are induced by information about the environment being communicated between components of the population via broadcast communication. We see how existing hybrid fluid limit results, resulting in piecewise deterministic Markov processes, can be adapted to such models. Finally, we propose heuristic constructions for extracting the mean behaviour from the resulting approximations without the need to simulate individual trajectories.
Original languageEnglish
Article number8
Number of pages26
JournalACM Transactions on Modeling and Computer Simulation
Issue number2
Publication statusPublished - 10 Feb 2021

Keywords / Materials (for Non-textual outputs)

  • fluid approximation
  • stochastic modelling
  • population dynamics
  • hybrid models


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