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Download Machine Learning Perspectives of ABM by Pedro Campos in PDF format completely FREE. No registration required, no payment needed. Get instant access to this valuable resource on PDFdrive.to!
About Machine Learning Perspectives of ABM
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 (AI), highlighting the advantages of each in modeling economic phenomena.
Detailed Information
| Author: | Pedro Campos |
|---|---|
| Pages: | 384 |
| Language: | English |
| File Size: | 14 |
| Format: | |
| Price: | FREE |
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