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Complexity and decision making

Grant number: 11/16971-0
Support Opportunities:Scholarships in Brazil - Master
Effective date (Start): March 01, 2012
Effective date (End): February 28, 2013
Field of knowledge:Physical Sciences and Mathematics - Physics - General Physics
Principal Investigator:Nestor Felipe Caticha Alfonso
Grantee:Eduardo Sangiorgio Dobay
Host Institution: Instituto de Física (IF). Universidade de São Paulo (USP). São Paulo , SP, Brazil


The project consists of two parts, both in the field of Decision Making, to be studied through the techniques of Statistical Mechanics and Information Theory.(1) Probability MatchingIn a task of successive choices from a binary random sequence without memory (Markov chain of order zero), the optimal strategy consists of repeatedly choosing the alternative with the largest frequency of occurrence. This optimal choice of strategy can be found in animal species including fishes and mice. However, several experiments show that members of the human species adopt chiefly the suboptimal strategy of adjusting the probability of choosing each option to its corresponding frequency, which is called "probability matching". This apparently suboptimal strategy seems to have been selected as an adaptation of organisms with greater cognitive capacity to environments with learnable regularities. The goal is to calculate error curves, as a function of the complexity of the underlying hypotheses in different experimental setups, and to compare them with data obtained by the group led by Prof. M. V. Baldo from ICB-USP.(2) Vitreous Dynamics and the Paradox of ChoiceWhen faced with too many choices a person can be led to unhappiness, indecision or paralysis. We propose to model this problem using ideas from attractor neural networks. We aim to verify how increasing the number of options leads to a vitreous dynamics.

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Academic Publications
(References retrieved automatically from State of São Paulo Research Institutions)
DOBAY, Eduardo Sangiorgio. Complexity of decision-making in human agents. 2014. Master's Dissertation - Universidade de São Paulo (USP). Instituto de Física (IF/SBI) São Paulo.

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