Gillespie Algorithms for Stochastic Multiagent Dynamics in Populations and Networks
Published on 21. December 2022
978-1-009-23913-4 (ISBN)
Description
Many multiagent dynamics can be modeled as a stochastic process in which the agents in the system change their state over time in interaction with each other. The Gillespie algorithms are popular algorithms that exactly simulate such stochastic multiagent dynamics when each state change is driven by a discrete event, the dynamics is defined in continuous time, and the stochastic law of event occurrence is governed by independent Poisson processes. The first main part of this volume provides a tutorial on the Gillespie algorithms focusing on simulation of social multiagent dynamics occurring in populations and networks. The authors clarify why one should use the continuous-time models and the Gillespie algorithms in many cases, instead of easier-to-understand discrete-time models. The remainder of the Element reviews recent extensions of the Gillespie algorithms aiming to add more reality to the model (i.e., non-Poissonian cases) or to speed up the simulations. This title is also available as open access on Cambridge Core.
More details
Series
Language
English
Place of publication
Cambridge
United Kingdom
Illustrations
Worked examples or Exercises
File size
3,47 MB
ISBN-13
978-1-009-23913-4 (9781009239134)
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Schweitzer Classification
Other editions
Additional editions
Naoki Masuda | Christian L. Vestergaard
Gillespie Algorithms for Stochastic Multiagent Dynamics in Populations and Networks
Book
01/2023
Cambridge University Press
€24.00
Shipment within 15-20 days
Persons
Content
1. Introduction; 2. Preliminaries; 3. Classic Gillespie Algorithms; 4. Computational Complexity and Efficient Implementations; 5. Gillespie Algorithms for Temporal Networks and Non-Poissonian Jump Processes; 6. Conclusions; References.
