research-article

Statistical Abstraction for Multi-scale Spatio-temporal Systems

Authors:

Michalis Michaelides,

Guido SanguinettiAuthors Info & Claims

ACM Transactions on Modeling and Computer Simulation (TOMACS), Volume 29, Issue 4

Article No.: 22, Pages 1 - 29

https://doi.org/10.1145/3366023

Published: 10 December 2019 Publication History

Abstract

Modelling spatio-temporal systems exhibiting multi-scale behaviour is a powerful tool in many branches of science, yet it still presents significant challenges. Here, we consider a general two-layer (agent-environment) modelling framework, where spatially distributed agents behave according to external inputs and internal computation; this behaviour may include influencing their immediate environment, creating a medium over which agent-agent interaction signals can be transmitted. We propose a novel simulation strategy based on a statistical abstraction of the agent layer, which is typically the most detailed component of the model and can incur significant computational cost in simulation. The abstraction makes use of Gaussian Processes, a powerful class of non-parametric regression techniques from Bayesian Machine Learning, to estimate the agent’s behaviour given the environmental input. We show on two biological case studies how this technique can be used to speed up simulations and provide further insights into model behaviour.

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Cited By

Çelik CBokes PSingh A(2020)Stationary Distributions and Metastable Behaviour for Self-regulating Proteins with General Lifetime DistributionsComputational Methods in Systems Biology10.1007/978-3-030-60327-4_2(27-43)Online publication date: 23-Sep-2020
https://dl.acm.org/doi/10.1007/978-3-030-60327-4_2
(2019)Introduction to the Special Issue on Qest 2017ACM Transactions on Modeling and Computer Simulation10.1145/336378429:4(1-2)Online publication date: 18-Nov-2019
https://dl.acm.org/doi/10.1145/3363784

Index Terms

Statistical Abstraction for Multi-scale Spatio-temporal Systems
1. Applied computing
  1. Life and medical sciences
    1. Systems biology
2. Theory of computation
  1. Logic
    1. Abstraction

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Published In

cover image ACM Transactions on Modeling and Computer Simulation

ACM Transactions on Modeling and Computer Simulation Volume 29, Issue 4

Special Issue On Qest 2017

October 2019

188 pages

ISSN:1049-3301

EISSN:1558-1195

DOI:10.1145/3372492

Editor:
Francesco Quaglia
University of Rome Tor Vergata, Italy

Issue’s Table of Contents

Copyright © 2019 ACM.

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New York, NY, United States

Publication Notes

Badge change: Article originally badged under Version 1.0 guidelines https://www.acm.org/publications/policies/artifact-review-badging

Publication History

Published: 10 December 2019

Accepted: 01 March 2019

Revised: 01 February 2019

Received: 01 January 2018

Published in TOMACS Volume 29, Issue 4

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Cited By

Çelik CBokes PSingh A(2020)Stationary Distributions and Metastable Behaviour for Self-regulating Proteins with General Lifetime DistributionsComputational Methods in Systems Biology10.1007/978-3-030-60327-4_2(27-43)Online publication date: 23-Sep-2020
https://dl.acm.org/doi/10.1007/978-3-030-60327-4_2
(2019)Introduction to the Special Issue on Qest 2017ACM Transactions on Modeling and Computer Simulation10.1145/336378429:4(1-2)Online publication date: 18-Nov-2019
https://dl.acm.org/doi/10.1145/3363784

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