Archivio per 2 settembre 2014

02
Set
14

Statistics Economics & Neuroscience: DECISION MAKING PROCESS: COMPONENTS AND TIME EFFECT

See on Scoop.itBounded Rationality and Beyond

We have seen [here] that the decision making activates a circuit, where the evaluation of the alternative solutions to a given problem and the choice of the best one would give rise to a learning mechanism for error reduction.  Now let’s talk about the main components which influence the decision making (see Figure 1). 

We can consider the combination of three factors over the decision making process:

the decision environment;the quantity of information;the decision stream.Figure 1. The components of decision making and the role of the time

Decision making is a process which requires the definition of the informative set (environment) by which select and implement the best solution to a given problem. During the decisional process the quantity of information is cumulated until a certain time (t’) beyond which the gathering of more information overload the decision maker. That is, the quantity of the “effective” information does not grow indefinitely, but will decrease from a certain time on. The existence of a time contraint enables the decision maker to get a decision. Decisions may have effect not only at the time when  they have been taken, but also may enter successive decisional processes, i.e., they may feed the decision environment of the same decision maker (or of other decision makers when we consider the social dynamics) in successive times. This flow of information forms the decision stream.   

See on statsneuro.blogspot.it

Annunci
02
Set
14

Statistics Economics & Neuroscience: A Two-Layered Diffusion Model Traces the Dynamics of Information Processing in the Valuation-and-Choice Circuit of Decision Making

See on Scoop.itBounded Rationality and Beyond

The evolution of the response-to-stimulus map is thus modeled by two linked diffusive modules (2LDM) representing the neuronal populations involved in the valuation-and-decision circuit of decision making (Figure 1). Diffusion models are naturally appropriate for describing accumulation of evidence over the time [see here]. This allows the computation of the response times (RTs) in valuation and choice, under the hypothesis of ex-Wald distribution. A nonlinear transfer function integrates the activities of the two layers. The input-output map based on the infomax principle makes the 2LDM consistent with the reinforcement learning approach. Results from simulated likelihood time series indicate that 2LDM may account for the activity-dependent modulatory component of effective connectivity between the neuronal populations. Rhythmic fluctuations of the estimate gain functions in the delta-beta bands also support the compatibility of 2LDM with the neurobiology of DM.

See on statsneuro.blogspot.it

02
Set
14

A Two-Layered Diffusion Model Traces the Dynamics of Information Processing in the Valuation-and-Choice Circuit of Decision Making

See on Scoop.itBounded Rationality and Beyond

Computational Intelligence and Neuroscience is a forum for the interdisciplinary field of neural computing, neural engineering and artificial intelligence, where neuroscientists, cognitive scientists, engineers, psychologists, physicists, computer scientists, and artificial intelligence investigators among others can publish their work in one periodical that bridges the gap between neuroscience, artificial intelligence and engineering.

See on hindawi.com

02
Set
14

Paving the Cow-Paths: The Demise of Idealism and the Pathway to Pragmatism

See on Scoop.itBounded Rationality and Beyond

Here’s an example: assuming that my book is sold by two shops. Shop A pays me royalties of 70% of the price of sales. Shop B gives me 100% of the price in royalties. Assuming both shops sell the book for the same price, my interest is to get as many sales as possible through shop B. However, Shop A(mazon) is more popular with the potential clients. Essentially I have two options. First, I can direct all my promotion effort to get sales through shop B and let whoever wants to buy from shop A to do so. Second, I could pave the cow-path and direct my promotion effort to encouraging people to buy from shop A, thus hoping that the higher volume of sales generated would compensate the lower percentage in royalties I get from each sale.

See on naumof.blogspot.nl




Time is real? I think not

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