A Simple Artificial Life Model Explains Irrational Behavior in Human Decision-Making

Although praised for their rationality, humans often make poor decisions, even in simple situations. In the repeated binary choice experiment, an individual has to choose repeatedly between the same two alternatives, where a reward is assigned to one of them with fixed probability. The optimal strategy is to perseverate with choosing the alternative with the best expected return. Whereas many species perseverate, humans tend to match the frequencies of their choices to the frequencies of the alternatives, a sub-optimal strategy known as probability matching. Our goal was to find the primary cognitive constraints under which a set of simple evolutionary rules can lead to such contrasting behaviors. We simulated the evolution of artificial populations, wherein the fitness of each animat (artificial animal) depended on its ability to predict the next element of a sequence made up of a repeating binary string of varying size. When the string was short relative to the animats' neural capacity, they could learn it and correctly predict the next element of the sequence. When it was long, they could not learn it, turning to the next best option: to perseverate. Animats from the last generation then performed the task of predicting the next element of a non-periodical binary sequence. We found that, whereas animats with smaller neural capacity kept perseverating with the best alternative as before, animats with larger neural capacity, which had previously been able to learn the pattern of repeating strings, adopted probability matching, being outperformed by the perseverating animats. Our results demonstrate how the ability to make predictions in an environment endowed with regular patterns may lead to probability matching under less structured conditions. They point to probability matching as a likely by-product of adaptive cognitive strategies that were crucial in human evolution, but may lead to sub-optimal performances in other environments.

Scientific research output evaluation of professors of Sao Paulo State University, Marilia/SP

In this work, an analysis of scientific bibliographic productivity was made using the Faculdade de Filosofia e Ciencias, Universidade Estadual Paulista (FFC-UNESP) as example. It is composed by nine departments which offer altogether nine undergraduate courses: 1) Archival, 2) Library, 3) Speech Therapy, 4) Pedagogy, 5) International Relations, 6) Physiotherapy, 7) Occupational Therapy, 8) Philosophy, 9) Social Sciences and six graduate programs leading to M. S. and Ph.D. degrees. Moreover, when analyzing the different courses of FFC-UNESP, they represent typical academic organization in Brazil and Latin America and could be taken as a model for analyzing other Brazilian research institutions. Using data retrieved from the Lattes Plataform database (Curriculum Lattes) we have quantitatively the scientific productivity percentage of professors at UNESP. We observed that bibliometric evaluations using the Curriculum Lattes (CL) showed that the professors published papers in journal are not indexed by ISI and SCOPUS. This analysis was made using: 1) the total number of papers (indexed in Curriculum Lattes database), 2) the number of papers indexed by Thomson ISI Web of Science database and SCOPUS database, and 3) the Hirsch (h-index) by ISI and SCOPUS. Bibliometric evaluations of departments showed a better performance of Political Science and Economics Department when compared to others departments, in relation total number of papers (indexed in Curriculum Lattes database). We also analyzed the academic advisory (Master's Thesis and Ph. D. Thesis) by nine departments of FFC/UNESP. The Administration and School Supervision Department presented a higher academic advisory (concluded and current) when compared to the others departments.

Análise da produtividade científica dos docentes da Universidade Estadual Paulista, campus de Marília/SP

O objetivo do presente trabalho foi analisar/quantificar a produtividade científica dos docentes pertencentes à Universidade de Estadual Paulista (UNESP), campus de Marília/SP. Para cada professor, analisamos o número total de artigos na plataforma Lattes, no ISI Web of Science e no SCOPUS. Além disso, verificamos o total de livros publicados, capítulos de livros publicados e orientações em Programas de Pós-Graduação (PPG). A análise dos nove departamentos da Faculdade de Filosofia e Ciências (FFC) mostrou que o Departamento de Ciências Políticas e Econômicas possui uma média elevada (21,42) de artigos na Plataforma Lattes, quando comparado aos outros departamentos. Entretanto, o Departamento de Fonoaudiologia apresentou médias mais altas em artigos indexados pelo ISI (2,61) e SCOPUS (4,39), bem como o índice-h, nessas plataformas. Em relação aos programas de pós-graduação, o Departamento de Administração e Supervisão Escolar foi o que apresentou a maior média de orientações em andamento e/ou concluídas. O desempenho mais baixo, em relação aos artigos publicados pelo ISI e SCOPUS, pelos departamentos na área de Humanas/Humanidades pode estar associado às características do campo da concentração e da cobertura limitada do banco de dados ISI e SCOPUS, indicando que o índice-h é muito sensível ao campo de concentração.