TWO STYLES OF NEUROECONOMICS

2008 ◽  
Vol 24 (3) ◽  
pp. 473-483 ◽  
Author(s):  
Don Ross

I distinguish between two styles of research that are both called “neuroeconomics”.Neurocellular economics(NE) uses the modelling techniques and mathematics of economics – constrained maximization and equilibrium analysis – to model relatively encapsulated functional parts of brains. This approach rests upon the fact that brains are, like markets, massively distributed information-processing networks over which executive systems can exert only limited and imperfect governance. Harrison's (2008) deepest criticisms of neuroeconomics do not apply to NE. However, the more famous style of neuroeconomics isbehavioural economics in the scanner. This is often motivated by complaints about conventional economics frequently heard from behavioural economists. It attempts to use neuroimaging data to justify arguments for replacing standard aspects of microeconomic theory by facts and conjectures about human psychology. Harrison's grounds for unease about neuroeconomics apply to most BES, or at least to its explicit methodology. This methodology is naively reductionist and illegitimately assumes that economics should not do what all successful science does, namely, model abstract aspects of its target phenomena instead of would-be complete and fully ecologically situated facsimiles of them.

Author(s):  
Г.А. Онтужева

В статье рассматривается возможность применения методов решения транспортной задачи к задаче распределения вычислительных ресурсов в гетерогенных распределенных системах обработки информации. Приведено сравнение эффективности алгоритмов с ранее разработанным алгоритмом наименьшего времени для атомарных заявок. The paper examines the applicability of methods for solving the transport problem to the problem of distribution of computing resources in heterogeneous distributed information processing systems. A comparison of the efficiency of the algorithms with the previously developed least time algorithm for atomic claims is given.


2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Hongli Dong ◽  
Zidong Wang ◽  
Steven X. Ding ◽  
Huijun Gao

In recent years, theoretical and practical research on large-scale networked systems has gained an increasing attention from multiple disciplines including engineering, computer science, and mathematics. Lying in the core part of the area are the distributed estimation and fault detection problems that have recently been attracting growing research interests. In particular, an urgent need has arisen to understand the effects of distributed information structures on filtering and fault detection in sensor networks. In this paper, a bibliographical review is provided on distributed filtering and fault detection problems over sensor networks. The algorithms employed to study the distributed filtering and detection problems are categorised and then discussed. In addition, some recent advances on distributed detection problems for faulty sensors and fault events are also summarized in great detail. Finally, we conclude the paper by outlining future research challenges for distributed filtering and fault detection for sensor networks.


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