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Bibliographies thématiques / Agent-based data simulation / Livres

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Livres sur le sujet « Agent-based data simulation »

Auteur : Grafiati

Publié le 9 mars 2023

Mis à jour le 11 mars 2023

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Consultez les 23 meilleurs livres pour votre recherche sur le sujet « Agent-based data simulation ».

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1

1950-, Arai K., Deguchi Hiroshi 1955-, Matsui H et International Simulation and Gaming Association. International Conference, dir. Agent-based modeling meets gaming simulation. Tokyo : Springer, 2005.

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2

Interdisciplinary applications of agent-based social simulation and modeling. Hershey, PA : Information Science Reference, 2014.

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3

International Workshop on Agent-Based Approaches in Economic and Social Complex Systems (3rd 2004 Kyoto, Japan). Agent-based simulation : From modeling methodologies to real-world applications : post-proceedings of the Third International Workshop on Agent-Based Approaches in Economic and Social Complex Systems 2004. Tokyo : Springer, 2005.

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4

S, Sichman Jaime, Bousquet François 1963- et Davidsson Paul 1964-, dir. Multi-agent-based simulation II : Third international workshop, MABS 2002, Bologna, Italy, July 2002 : revised papers. Berlin : Springer, 2003.

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5

David, Hales, dir. Multi-agent-based simulation III : 4th international workshop, MABS 2003, Melbourne, Australia, July 14, 2003 : revised papers. Berlin : Springer, 2003.

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6

Luis, Antunes, Norling Emma, Paolucci Mario, Siekmann Jörg H et SpringerLink (Online service), dir. Multi-Agent-Based Simulation VIII : International Workshop, MABS 2007, Honolulu, HI, USA, May 15, 2007, Revised and Invited Papers. Berlin, Heidelberg : Springer-Verlag Berlin Heidelberg, 2008.

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7

David, Hutchison. Multi-Agent-Based Simulation IX : International Workshop, MAPS 2008, Estoril, Portugal, May 12-13, 2008, Revised Selected Papers. Berlin, Heidelberg : Springer Berlin Heidelberg, 2009.

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8

1959-, Chen Shu-Heng, Terano Takao 1952- et Yamamoto Ryūichi, dir. Agent-based approaches in economic and social complex systems VI : Post-proceedings of the AESCS International Workshop 2009 / Shu-Heng Chen, Takao Terano, Ryuichi Yamamoto, editors. Tokyo : Springer, 2011.

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9

Wurzer, Gabriel, Kerstin Kowarik et Hans Reschreiter. Agent-Based Modeling and Simulation in Archaeology. Springer, 2014.

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10

Wurzer, Gabriel, Kerstin Kowarik et Hans Reschreiter. Agent-based Modeling and Simulation in Archaeology. Springer, 2016.

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11

Wurzer, Gabriel, Kerstin Kowarik et Hans Reschreiter. Agent-based Modeling and Simulation in Archaeology. Springer, 2014.

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12

(Editor), K. Arai, H. Deguchi (Editor) et H. Matsui (Editor), dir. Agent-Based Modeling Meets Gaming Simulation (Springer Series on Agent Based Social Systems). Springer, 2006.

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13

Agent-based modeling meets gaming simulation. Tokyo, Japan : Springer, 2006.

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14

(Editor), Paul Davidsson, Brian Logan (Editor) et Keiki Takadama (Editor), dir. Multi-Agent and Multi-Agent-Based Simulation : Joint Workshop MABS 2004 (Lecture Notes in Computer Science). Springer, 2005.

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15

Agent-based Models of the Economy : From Theories to Applications. Palgrave Macmillan, 2015.

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16

Boero, R., M. Morini, M. Sonnessa et P. Terna. Agent-Based Models of the Economy : From Theories to Applications. Palgrave Macmillan Limited, 2015.

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17

Fent, Thomas, Francesco C. Billari, Jürgen Scheffran et Alexia Prskawetz. Agent-Based Computational Modelling : Applications in Demography, Social, Economic and Environmental Sciences. Springer London, Limited, 2006.

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18

1976-, Rand William, dir. An introduction to agent-based modeling : Modeling natural, social, and engineered complex systems with NetLogo. The MIT Press, 2015.

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19

(Editor), Francesco C. Billari, Thomas Fent (Editor), Alexia Prskawetz (Editor) et Jürgen Scheffran (Editor), dir. Agent-Based Computational Modelling : Applications in Demography, Social, Economic and Environmental Sciences (Contributions to Economics). Physica-Verlag Heidelberg, 2006.

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20

Sichman, Jaime S., et Luis Antunes. Multi-Agent-Based Simulation VI : International Workshop, MABS 2005, Utrecht, the Netherlands, July 25, 2005, Revised and Invited Papers. Springer London, Limited, 2006.

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21

(Editor), Jaime S. Sichman, et Luis Antunes (Editor), dir. Multi-Agent-Based Simulation VI : International Workshop, MABS 2005, Utrecht, The Netherlands, July 25, 2005, Revised and Invited Papers (Lecture Notes in Computer Science). Springer, 2006.

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22

Monge, Peter R., et Noshir Contractor. Theories of Communication Networks. Oxford University Press, 2003. http://dx.doi.org/10.1093/oso/9780195160369.001.0001.

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To date, most network research contains one or more of five major problems. First, it tends to be atheoretical, ignoring the various social theories that contain network implications. Second, it explores single levels of analysis rather than the multiple levels out of which most networks are comprised. Third, network analysis has employed very little the insights from contemporary complex systems analysis and computer simulations. Foruth, it typically uses descriptive rather than inferential statistics, thus robbing it of the ability to make claims about the larger universe of networks. Finally, almost all the research is static and cross-sectional rather than dynamic. Theories of Communication Networks presents solutions to all five problems. The authors develop a multitheoretical model that relates different social science theories with different network properties. This model is multilevel, providing a network decomposition that applies the various social theories to all network levels: individuals, dyads, triples, groups, and the entire network. The book then establishes a model from the perspective of complex adaptive systems and demonstrates how to use Blanche, an agent-based network computer simulation environment, to generate and test network theories and hypotheses. It presents recent developments in network statistical analysis, the p* family, which provides a basis for valid multilevel statistical inferences regarding networks. Finally, it shows how to relate communication networks to other networks, thus providing the basis in conjunction with computer simulations to study the emergence of dynamic organizational networks.

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23

Humphreys, Paul. Computational Economics. Sous la direction de Don Ross et Harold Kincaid. Oxford University Press, 2009. http://dx.doi.org/10.1093/oxfordhb/9780195189254.003.0013.

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Computational economics is a relatively new research technique in economics, but it is inexorably taking its place alongside the more traditional methods of general theory, abstract modeling, data analysis, and the more recent experimental economics. Perhaps because of its relative newness, the term computational economics currently has no determinate meaning. In contemporary use, it refers to a heterogeneous cluster of techniques implemented on concrete digital computers ranging from the numerical solution of the Black-Scholes partial differential equation for pricing options through automated trading strategies to agent-based computer simulations of the evolution of cooperation. Because of this heterogeneity, it is not possible to provide a comprehensive coverage of the topic in this article. Another reason for this restricted scope is that many of the methods used in computational economics have considerable technical interest but no particular philosophical relevance.

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