Archivio per 5 settembre 2014

05
Set
14

NeuroEconomia: Come il Cervello prende le Decisioni – Video Corso

See on Scoop.itBounded Rationality and Beyond

Economia, Psicologia e Neuroscienze stanno oggi convergendo in una nuova disciplina chiamata Neuroeconomia, con l’obiettivo di fornire una unica teoria generale dei processi decisionali umani.

La Neuroeconomia offre a economisti, psicologi e scienziati sociali una più profonda comprensione di come l’uomo prendere le decisioni, partendo dal presupposto che, a differenza di quanto affermato dall’economia tradizionale,l’uomo non è un animale razionale, ma agisce sotto l’impulso di processi neuronali automatici e molto spesso inconsci, quindi indipendenti dalla propria volontà. 

Il cervello é programmato per prendere rischi o per evitarli ? Come è valutata dal cervello una “decisione giusta” ? E possibile prevedere le intenzioni di acquisto di un consumatore ? Possiamo modulare il comportamento del cervello riguardo gli aspetti economici ?

Per rispondere a queste domande e conoscere meglio le basi della Neuroeconomia a partire dal prossimo 23 Giugno la prestigiosa Higher School of Economics di Mosca, presenta un nuovo interessante video corso di 9 settimanetotalmente gratuito, intitolato Introduction to Neuroeconomics: how the brain makes decisions che tratterà molti argomenti partendo dai fondamenti della neuroeconomia e neuroanatomia del cervello trattati in quattro moduli successivi, guarda la video-presentazione del corso :

See on abtechno.org

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05
Set
14

Rumor-Propagation Model with Consideration of Refutation Mechanism in Homogeneous Social Networks

See on Scoop.itBounded Rationality and Beyond

The main objective of Discrete Dynamics in Nature and Society is to foster links between basic and applied research relating to discrete dynamics of complex systems encountered in the natural and social sciences. The journal intends to stimulate publications directed to the analyses of computer generated solutions and chaotic in particular, correctness of numerical procedures, chaos synchronization and control, discrete optimization methods among other related topics. The journal provides a channel of communication between scientists and practitioners working in the field of complex systems analysis and will stimulate the development and use of discrete dynamical approach.

See on hindawi.com

05
Set
14

The evolution of nonlinear dynamics in political science and public administration: Methods, modeling and momentum

See on Scoop.itBounded Rationality and Beyond

The main objective of Discrete Dynamics in Nature and Society is to foster links between basic and applied research relating to discrete dynamics of complex systems encountered in the natural and social sciences. The journal intends to stimulate publications directed to the analyses of computer generated solutions and chaotic in particular, correctness of numerical procedures, chaos synchronization and control, discrete optimization methods among other related topics. The journal provides a channel of communication between scientists and practitioners working in the field of complex systems analysis and will stimulate the development and use of discrete dynamical approach.

See on hindawi.com

05
Set
14

Chaos and Politics: Applications of Nonlinear Dynamics to Socio-Political Issues

See on Scoop.itBounded Rationality and Beyond

Abstract: We discuss the extent to which recent improvements in our understanding of inherently nonlinear phenomena present challenges to the use of mathematical models in the analysis of environmental and socio-political issues. In particular, we demonstrate that the “deterministic chaos” present in many nonlinear systems can impose fundamental limitations on our ability to predict behavior even when precisely defined mathematical models exist. On the other hand, results from chaos theory can provide means for better accuracy for short-term predictions even for systems which appear to behave completely randomly. Chaos also provides a new paradigm of a complex temporal evolution with bounded growth and limited resources without the equivalent of stagnation and decay. This is in contrast to a traditional view of historical evolution which is perhaps best expressed by the phrase: “if something stops growing, it starts rotting.” The exploration of a large number of states by a single deterministic solution creates the potential for adaptation and evolution. In the context of artificial life models this has led to the notion of “Life at the edge of chaos” expressing the principle that a delicate balance of chaos and order is optimal for successful evolution. Since our primary aim is didactic, we make no attempt to treat realistic models for complex issues but rather introduce a sequence of simple models which illustrate the increasingly complicated behavior that can arise when the nonlinearity is properly taken into account. We begin with the familiar elementary model of population growth originally due to Malthus and indicate how the incorporation of nonlinear effects alters dramatically the expected dynamics of the populations. We then discuss models which are caricatures of two issues–weather prediction and international arms races. Among the arms race models we consider a special class which is related to population dynamcis and which is first introduced by L. F. Richardson after WW I. The examples we discuss, however, have discrete time dependence. For certain ranges of their control parameters, these models exhibit “deterministic chaos,” and we discuss how this behavior limits our ability to anticipate and predict the outcomes of various situations. We then briefly describe methods to exploit the high sensitivity of chaotic systems to dramatically increase the capability of both forecasting and control of chaotic systems. We show that many different solutions can coexist even in simple models and how machine learning methods such as neural nets and genetic algorithms can be used to find classes of optimal solutions. We speculate on some generalizations of arms control models into object oriented frameworks which allow simultaneous modeling on different levels of quantitative formalizations: In a computational network we can have nodes which represent purely conceptual models of areas where quantitative analysis would be inappropriate and other nodes for which a hierarchical structure of mls of arbitrary quantitative detail and sophistication can be generated. Finally, we close with a few remarks on our general theme, stressing that, despite its limitations and because of its challenges, mathematical modeling of complex environmental and socio-political issues is crucial to any efforts to use technology to enhance international stability and cooperation.

See on santafe.edu

05
Set
14

Psychological Incentives, Financial Incentives, and Risk Attitudes in Tournaments An Artefactual Field Experiment

See on Scoop.itBounded Rationality and Beyond

Abstract

Tournaments are widely used to assign bonuses and determine promotions. Tournament-based compensation is motivating because of the link between relative performance and financial

rewards. However, performing relatively well (poorly) may also yield psychological benefits (pain). This may also stimulate effort. Through a real-effort artefactual field experiment with factory workers in China, we examine how both psychological and financial incentives, together with attitudes toward risk, may influence motivation and performance. For comparison purposes, Chinese undergraduate students also participated in a comparable laboratory experiment. We provided performance-ranking information both privately and publicly, with and without rankbased

financial incentives. Our results show that performance-ranking information had a significant motivational effect on average performance for students, but not for workers. Adding financial incentives based on rank provided little evidence of further improvements. Much of the difference between workers and students can be explained by differences in attitudes toward risk.

Indeed, for both groups the size of both financial and psychological incentive effects is inversely related to individual levels of risk aversion, and is positive and significant both for workers and

for students who are sufficiently risk-tolerant. Lastly, performance did not deteriorate when incentives were removed, suggesting that they worked through the encouragement of learning.

See on uoguelph.ca

05
Set
14

Direct Brain-to-Brain Communication Demonstrated Over The Internet — PsyBlog

See on Scoop.itBounded Rationality and Beyond

An international team of roboticists and neuroscientists have demonstrated brain-to-brain communication between two people over the internet for the first time. Professor Alvaro Pascual-Leone, of Harvard Medical School, explained the thinking behind the study: “We wanted to find out if one could communicate directly between two people by reading out the brain activity from one person and injecting brain activity into the second person, and do so across great physical distances by leveraging existing communication pathways.” “One such pathway is, of course, the internet, so our question became, ‘Could we develop an experiment that would bypass the talking or typing part of internet and establish direct brain-to-brain communication between subjects located far away from each other in India and France?’” The scientists in France and Spain used EEG (electroencephalogram) and TMS (transcranial magnetic stimulation) technology (Grau et al., 2014).

See on spring.org.uk

05
Set
14

The Precautionary Principle: Fragility and Blac Swans from Policy Actions

See on Scoop.itBounded Rationality and Beyond

Abstract—The precautionary principle (PP) states that if an action

or policy has a suspected risk of causing severe harm to the public

domain (affecting general health or the environment globally), the action should not be taken in the absence of scientific near-certainty about its safety. Under these conditions, the burden of proof about absence of harm falls on those proposing an action, not those opposing it. PP is intended to deal with uncertainty and risk in cases where the absence of evidence and the incompleteness of scientific knowledge carries profound implications and in the presence of risks of “black swans”,

unforeseen and unforeseable events of extreme consequence.

This non-naive version of the PP allows us to avoid paranoia and

paralysis by confining precaution to specific domains and problems. Here we formalize PP, placing it within the statistical and probabilistic structure of “ruin” problems, in which a system is at risk of total failure, and in place of risk we use a formal"fragility" based approach. In these problems, what appear to be small and reasonable risks accumulate inevitably to certain irreversible harm. Traditional cost-benefit analyses, which seek to quantitatively weigh outcomes to determine the best

policy option, do not apply, as outcomes may have infinite costs. Even high-benefit, high-probability outcomes do not outweigh the existence of low probability, infinite cost options—i.e. ruin. Uncertainties result in sensitivity analyses that are not mathematically well behaved. The PP is increasingly relevant due to man-made dependencies that propagate impacts of policies across the globe. In contrast, absent humanity the biosphere engages in natural experiments due to random variations

with only local impacts. Our analysis makes clear that the PP is essential for a limited set of contexts and can be used to justify only a limited set of actions. We discuss the implications for nuclear energy and GMOs. GMOs represent a public risk of global harm, while harm from nuclear energy is comparatively limited and better characterized. PP should be used to prescribe severe limits on GMOs

See on docs.google.com




Time is real? I think not

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