Christian L. Vestergaard, Naoki Masuda Gillespie Algorithms for Stochastic Multiagent Dynamics in Populations and Networks 9781009239141

Варианты приобретения

Цена: 2851.00р.
Кол-во:
Наличие: Поставка под заказ. Есть в наличии на складе поставщика.
Склад Америка: Есть
При оформлении заказа до: 2026-05-14
Ориентировочная дата поставки: Июнь
При условии наличия книги у поставщика.

Добавить в корзину

в Мои желания

Автор: Christian L. Vestergaard, Naoki Masuda
Название: Gillespie Algorithms for Stochastic Multiagent Dynamics in Populations and Networks
ISBN: 9781009239141
Издательство: Cambridge Academ
Классификация:

Математическая физика

ISBN-10: 1009239147
Обложка/Формат: Paperback
Страницы: 106
Вес: 0.17 кг.
Дата издания: 05.01.2023
Серия: Elements in the structure and dynamics of complex networks
Язык: English
Иллюстрации: Worked examples or exercises
Размер: 222 x 145 x 20
Читательская аудитория: General (us: trade)
Ключевые слова: Discrete mathematics,Mathematical physics,Maths for computer scientists,Statistical physics, SCIENCE / Physics / Mathematical & Computational
Ссылка на Издательство: Link
Рейтинг:
Поставляется из: Англии
Описание: 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.

Gillespie Algorithms for Stochastic Multiagent Dynamics in Populations and Networks, Christian L. Vestergaard, Naoki Masuda