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Gillespie Algorithms for Stochastic Multiagent Dynamics in Populations and Networks
Published by Cambridge University Press, 2023
ISBN 10: 1009239147 ISBN 13: 9781009239141
Language: English
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Gillespie Algorithms for Stochastic Multiagent Dynamics in Populations and Networks (Paperback or Softback)
Published by Cambridge University Press 1/5/2023, 2023
ISBN 10: 1009239147 ISBN 13: 9781009239141
Language: English
Paperback or Softback. Condition: New. Gillespie Algorithms for Stochastic Multiagent Dynamics in Populations and Networks 0.34. Book.
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Gillespie Algorithms for Stochastic Multiagent Dynamics in Populations and Networks (Elements in the Structure and Dynamics of Complex Networks)
Published by Cambridge University Press, 2023
ISBN 10: 1009239147 ISBN 13: 9781009239141
Language: English
Condition: New.
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Gillespie Algorithms for Stochastic Multiagent Dynamics in Populations and Networks (Elements in the Structure and Dynamics of Complex Networks)
Published by Cambridge University Press, 2023
ISBN 10: 1009239147 ISBN 13: 9781009239141
Language: English
Condition: New. SUPER FAST SHIPPING.
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Gillespie Algorithms for Stochastic Multiagent Dynamics in Populations and Networks
Published by Cambridge University Press, 2023
ISBN 10: 1009239147 ISBN 13: 9781009239141
Language: English
US$ 27.72
Convert currencyUS$ 2.64 shipping within U.S.A.Quantity: Over 20 available
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Gillespie Algorithms for Stochastic Multiagent Dynamics in Populations and Networks (Paperback)
Published by Cambridge University Press, Cambridge, 2023
ISBN 10: 1009239147 ISBN 13: 9781009239141
Language: English
Paperback. Condition: new. 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 multiple locations in the US or from the UK, depending on stock availability.
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Gillespie Algorithms for Stochastic Multiagent Dynamics in Populations and Networks
Published by Cambridge University Press, 2023
ISBN 10: 1009239147 ISBN 13: 9781009239141
Language: English
Condition: New.
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Gillespie Algorithms for Stochastic Multiagent Dynamics in Populations and Networks
Published by Cambridge University Press, 2023
ISBN 10: 1009239147 ISBN 13: 9781009239141
Language: English
US$ 26.28
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Gillespie Algorithms for Stochastic Multiagent Dynamics in Populations and Networks (Elements in the Structure and Dynamics of Complex Networks)
Published by Cambridge University Press, 2023
ISBN 10: 1009239147 ISBN 13: 9781009239141
Language: English
US$ 40.37
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Gillespie Algorithms for Stochastic Multiagent Dynamics in Populations and Networks
Published by Cambridge University Press, 2023
ISBN 10: 1009239147 ISBN 13: 9781009239141
Language: English
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Gillespie Algorithms for Stochastic Multiagent Dynamics in Populations and Networks (Elements in the Structure and Dynamics of Complex Networks)
Published by Cambridge University Press, 2023
ISBN 10: 1009239147 ISBN 13: 9781009239141
Language: English
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Gillespie Algorithms for Stochastic Multiagent Dynamics in Populations and Networks
Published by Cambridge University Press 2022-12, 2022
ISBN 10: 1009239147 ISBN 13: 9781009239141
Language: English
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Gillespie Algorithms for Stochastic Multiagent Dynamics in Populations and Networks
Published by Cambridge University Press, 2023
ISBN 10: 1009239147 ISBN 13: 9781009239141
Language: English
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
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Gillespie Algorithms for Stochastic Multiagent Dynamics in Populations and Networks
Published by Cambridge University Press, 2023
ISBN 10: 1009239147 ISBN 13: 9781009239141
Language: English
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
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Gillespie Algorithms for Stochastic Multiagent Dynamics in Populations and Networks
Published by Cambridge University Press, 2023
ISBN 10: 1009239147 ISBN 13: 9781009239141
Language: English
US$ 35.89
Convert currencyUS$ 33.77 shipping from United Kingdom to U.S.A.Quantity: 2 available
Add to basketPaperback. Condition: Brand New. 106 pages. 9.00x6.00x0.22 inches. In Stock.
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Gillespie Algorithms for Stochastic Multiagent Dynamics in Populations and Networks (Paperback)
Published by Cambridge University Press, Cambridge, 2023
ISBN 10: 1009239147 ISBN 13: 9781009239141
Language: English
US$ 45.21
Convert currencyUS$ 37.00 shipping from Australia to U.S.A.Quantity: 1 available
Add to basketPaperback. Condition: new. 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 Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Gillespie Algorithms for Stochastic Multiagent Dynamics in Populations and Networks (Paperback)
Published by Cambridge University Press, Cambridge, 2023
ISBN 10: 1009239147 ISBN 13: 9781009239141
Language: English
US$ 35.46
Convert currencyUS$ 49.98 shipping from United Kingdom to U.S.A.Quantity: 1 available
Add to basketPaperback. Condition: new. 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.
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Gillespie Algorithms for Stochastic Multiagent Dynamics in Populations and Networks
Published by Cambridge University Press, 2023
ISBN 10: 1009239147 ISBN 13: 9781009239141
Language: English
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
US$ 27.49
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Add to basketPaperback / softback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 170.
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Gillespie Algorithms for Stochastic Multiagent Dynamics in Populations and Networks
Published by Cambridge University Press, 2023
ISBN 10: 1009239147 ISBN 13: 9781009239141
Language: English
US$ 24.39
Convert currencyUS$ 33.77 shipping from United Kingdom to U.S.A.Quantity: 1 available
Add to basketPaperback. Condition: Brand New. 106 pages. 9.00x6.00x0.22 inches. In Stock. This item is printed on demand.
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Add to basketCondition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Inhaltsverzeichnis1. 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. Conclusi.
