mso-fareast-language: EN-US;">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.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Anand Rao is a Distinguished Services Professor of Applied Data Science and AI in the Heinz College of Information Systems and Public Policy at Carnegie Mellon University. He received his PhD from the University of Sydney (with a University Postgraduate Research Award-UPRA) in 1988 and an MBA (with Award of Distinction) from Melbourne Business School in 1997. He boasts a 35-year career spanning AI, data, and analytics, serving as PwC's Global AI Leader. His research focuses on operationalizing AI, responsible AI, and agent-based models. Recognized globally, he has received accolades such as the Most Influential Paper Award and distinctions in AI and InsureTech. Prior to joining management consulting, he was the Chief Research Scientist at the Australian Artificial Intelligence Institute, where he built agent-based models and simulation systems and conducted research in the theory and practice of multi-agent systems.
Pedro Campos, PhD in Business Sciences (2008), with a background in Mathematics and Statistics, is Associate Professor of the Faculty of Economics, University of Porto, and conducts his research at LIAAD, the Artificial Intelligence and Decision Analysis Laboratory of INESC TEC. He currently serves as the Director of Methodology Services at Statistics Portugal. He specializes in Statistics, Data Science, Network Mining, and Marketing Research. Some of his research contributions delve into Innovation and Employment, Collaborative Networks, and Data Visualization. He has more than 50 publications, including articles in specialized journals and book chapters, and has edited 3 books. Pedro is also Deputy Director of the ISLP (International Statistical Literacy Project).
Joaquim Margarido, an ISEP (Superior Institute of Engineering of Porto) graduate, holds a master's degree in multi-agent systems. With expertise in IT, he imparts knowledge in programming using Java, Python, C#, SQL, and web technologies. Dedicated to practical solutions, Joaquim has developed software for various companies, addressing common challenges. His commitment to innovative software solutions reflects his extensive training and proficiency in diverse programming languages, contributing to both education and industry.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Vendeur : Brook Bookstore On Demand, Napoli, NA, Italie
Etat : new. Questo è un articolo print on demand. N° de réf. du vendeur MXKXXQCJ2R
Quantité disponible : Plus de 20 disponibles
Vendeur : California Books, Miami, FL, Etats-Unis
Etat : New. N° de réf. du vendeur I-9783031733536
Quantité disponible : Plus de 20 disponibles
Vendeur : AussieBookSeller, Truganina, VIC, Australie
Hardcover. Etat : new. Hardcover. 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. mso-fareast-language: EN-US;">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. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. N° de réf. du vendeur 9783031733536
Quantité disponible : 1 disponible(s)
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This bookprovides 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 ofheterogeneous 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 bookexplores 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. 377 pp. Englisch. N° de réf. du vendeur 9783031733536
Quantité disponible : 2 disponible(s)
Vendeur : moluna, Greven, Allemagne
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. N° de réf. du vendeur 1829341634
Quantité disponible : Plus de 20 disponibles
Vendeur : Grand Eagle Retail, Bensenville, IL, Etats-Unis
Hardcover. Etat : new. Hardcover. 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. mso-fareast-language: EN-US;">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. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9783031733536
Quantité disponible : 1 disponible(s)
Vendeur : preigu, Osnabrück, Allemagne
Buch. Etat : Neu. Machine Learning Perspectives of Agent-Based Models | Practical Applications to Economic Crises and Pandemics with Python, R, Netlogo and Julia | Pedro Campos (u. a.) | Buch | xx | Englisch | 2025 | Springer | EAN 9783031733536 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. N° de réf. du vendeur 130113256
Quantité disponible : 5 disponible(s)
Vendeur : CitiRetail, Stevenage, Royaume-Uni
Hardcover. Etat : new. Hardcover. 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. mso-fareast-language: EN-US;">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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9783031733536
Quantité disponible : 1 disponible(s)
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Buch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 400 pp. Englisch. N° de réf. du vendeur 9783031733536
Quantité disponible : 1 disponible(s)
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This bookprovides 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 ofheterogeneous 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 bookexplores 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. N° de réf. du vendeur 9783031733536
Quantité disponible : 1 disponible(s)