Titlebook: Collectives and the Design of Complex Systems; Kagan Tumer,David Wolpert Book 2004 Springer Science+Business Media New York 2004 algorithm

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纪念

Managing Catastrophic Changes in a Collective,he information concerning such large macroscopic changes becomes encoded in the microscopic dynamics. Our findings suggest that these large endogenous changes can be avoided either by pre-design of the collective machinery itself or in the postdesign stage via continual monitoring and occasional “vaccinations.”

一小块

Book 2004ely high­ dimensional spaces. Given the difficulty of performing such high-dimensional op­ timization with modern computers, there has been a lot of exploration of computa­ tional algorithms that try to emulate those naturally-occurring function optimizers. Examples include simulated annealing (SA [

铁砧

https://doi.org/10.1007/978-3-319-23648-3e of system dynamics and because the computational cost of implementing particular equilibrium outcomes is also important. We discuss some of these challenges and provide a reinterpretation of the mathematics of collective intelligence in terms of . for bounded-rational agents.

钩针织物

https://doi.org/10.1007/978-3-319-23648-3all we can do is to adjust the ways in which the agents interact with each other and the system in order to achieve our own design goals. In game theory, this is the mechanism design problem, and the design goal is denoted the “social choice function” (SCF). .

钩针织物

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viewed as function optimizers. In particular, they can be viewed as such optimizers of functions in extremely high­ dimensional spaces. Given the difficulty of performing such high-dimensional op­ timization with modern computers, there has been a lot of exploration of computa­ tional algorithms th

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