By Frédéric Amblard, Francisco J. Miguel, Adrien Blanchet, Benoit Gaudou
The publication provides a peer-reviewed selection of papers provided in the course of the tenth factor of the bogus Economics convention, addressing a number of concerns concerning macroeconomics, business association, networks, administration and finance, in addition to in basic terms methodological matters. the sphere of synthetic economics covers a wide diversity of methodologies counting on computing device simulations for you to version and learn the complexity of financial and social phenomena. The grounding precept of synthetic economics is the research of mixture homes of simulated structures populated by means of interacting adaptive brokers which are outfitted with heterogeneous person behavioral ideas. those macroscopic houses are neither foreseen nor meant via the substitute brokers yet generated jointly through them. they're rising features of such artificially simulated systems.
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Extra resources for Advances in Artificial Economics
Physica A 370(1):81–85 Snyman JA (2005) Practical mathematical optimization: an introduction to basic optimization theory and classical and new gradient-based algorithms. Springer, Heidelberg Waltman L, Kaymak U (2008) Q-learning agents in a Cournot oligopoly model. J Econ Dyn Control 32(10):3275–3293 Wilensky U (1999) NetLogo. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston. edu/netlogo/ Organizational Change for Its Own Sake? Results of an Agent-Based Simulation Friederike Wall 1 Introduction The dissemination of organizational design elements changes over time, and the popularity of some management techniques seems to follow a cyclic pattern.
Int Econ Rev 45(1):205–224 Keen S, Standish R (2006) Profit maximization, industry structure, and competition: a critique of neoclassical theory. Physica A 370(1):81–85 Snyman JA (2005) Practical mathematical optimization: an introduction to basic optimization theory and classical and new gradient-based algorithms. Springer, Heidelberg Waltman L, Kaymak U (2008) Q-learning agents in a Cournot oligopoly model. J Econ Dyn Control 32(10):3275–3293 Wilensky U (1999) NetLogo. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston.
However, in case of cross-departmental interactions, choices of department r might affect the contributions of the other departments’ choices and vice versa. The elements of the model described so far, capture the size N of the decision problem d an organization faces, the level K of interactions among the single decisions, the segmentation of d into sub-problems and the sub-problems’ delegation to r departments and, finally, how the organizational performance V results from a certain configuration d.
Advances in Artificial Economics by Frédéric Amblard, Francisco J. Miguel, Adrien Blanchet, Benoit Gaudou