Gillespie Algorithms for Stochastic Multiagent Dynamics in Populations and Networks (Paperback)

Naoki Masuda

ISBN 10: 1009239147 / ISBN 13: 9781009239141

Edité par Cambridge University Press, Cambridge, 2023

A propos de cet article

Paperback. 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. This Element provides a tutorial on the Gillespie algorithms focusing on social multiagent dynamics and also review their recent extensions. The first main part focuses on simulation of social multiagent dynamics occurring in populations and networks, and the remainder reviews recent extensions of the Gillespie algorithms. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

N° de réf. du vendeur 9781009239141

Détails bibliographiques

• Titre: Gillespie Algorithms for Stochastic Multiagent Dynamics in Populations and Networks (Paperback)
• Éditeur: Cambridge University Press, Cambridge
• Date de parution: 2023
• Langue: anglais
• ISBN à 10 chiffres: 1009239147
• ISBN à 13 chiffres: 9781009239141
• Reliure: Paperback
• État de l'article: new

A propos de ce titre

Synopsis

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.