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Gillespie algorithms for stochastic multiagent dynamics in populations and networks /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Gillespie algorithms for stochastic multiagent dynamics in populations and networks // Naoki Masuda, Christian L. Vestergaard.
Author:	Masuda, Naoki,
other author:	Vestergaard, Christian L.,
Description:	1 online resource (96 pages) :digital, PDF file(s). :
Notes:	Title from publisher's bibliographic system (viewed on 19 Dec 2022).
Subject:	Algorithms. -
Online resource:	https://doi.org/10.1017/9781009239158
ISBN:	9781009239158 (ebook)

Gillespie algorithms for stochastic multiagent dynamics in populations and networks /
Masuda, Naoki,1976-

Gillespie algorithms for stochastic multiagent dynamics in populations and networks /Naoki Masuda, Christian L. Vestergaard. - 1 online resource (96 pages) :digital, PDF file(s). - Cambridge elements. Elements in the structure and dynamics of complex networks,. - Cambridge elements.Elements in the structure and dynamics of complex networks,.

Title from publisher's bibliographic system (viewed on 19 Dec 2022).

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.

ISBN: 9781009239158 (ebook)Subjects--Topical Terms:

527865
Algorithms.

LC Class. No.: QA9.58 / .M37 2022

Dewey Class. No.: 518.1

Gillespie algorithms for stochastic multiagent dynamics in populations and networks /
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500 $a Title from publisher's bibliographic system (viewed on 19 Dec 2022).
520 $a 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.
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