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books
| book details |
Machine Learning Perspectives of Agent-Based Models: Practical Applications to Economic Crises and Pandemics with Python, R, Netlogo and Julia
Edited by Pedro Campos, Edited by Anand Rao, Edited by Joaquim Margarido
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| on special |
normal price: R 4 752.95
Price: R 4 515.95
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| book description |
This book provides an overview of agent-based modeling (ABM) and multi-agent systems (MAS), emphasizing their significance in understanding complex economic systems, with a special focus on the emerging properties of heterogeneous agents that cannot be deduced from the characteristics of individual agents. ABM is highlighted as a powerful tool for studying economics, especially in the context of financial crises and pandemics, where traditional models, such as dynamic stochastic general equilibrium (DSGE) models, have proven inadequate. Containing numerous practical examples and applications with R, Python, Julia and Netlogo, the book explores how learning, particularly machine learning, can be integrated into multi-agent systems to enhance the adaptation and behavior of agents in dynamic environments. It compares different learning approaches, including game theory and artificial intelligence, highlighting the advantages of each in modeling economic phenomena.
| product details |
Normally shipped |
Publisher | Springer International Publishing AG
Published date | 19 Aug 2025
Language |
Format | Hardback
Pages | 377
Dimensions | 235 x 155 x 0mm (L x W x H)
Weight | 0g
ISBN | 978-3-0317-3353-6
Readership Age |
BISAC | mathematics / probability & statistics / general
| other options |
Normally shipped |
Readership Age |
Normal Price | R 6 595.95
Price | R 6 266.95
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Carlo Rovelli
Paperback / softback
208 pages
was: R 295.95
now: R 265.95
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Carlo Rovelli
Paperback / softback
224 pages
was: R 295.95
now: R 265.95
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Originally published in Italian: L'ordine del tempo (Milan: Adelphi Edizioni, 2017).
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