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Agent based models: learning in neural networks and emerging collective properties

Grant number: 20/00021-1
Support type:Scholarships in Brazil - Scientific Initiation
Effective date (Start): March 01, 2020
Effective date (End): February 28, 2021
Field of knowledge:Physical Sciences and Mathematics - Physics - General Physics
Principal Investigator:Nestor Felipe Caticha Alfonso
Grantee:Ian Lucas Ramos de Carvalho dos Santos Pinto
Home Institution: Instituto de Física (IF). Universidade de São Paulo (USP). São Paulo , SP, Brazil

Abstract

The student will enter into a research project that deals with (I) learning in neural networks and (II) the construction and characterization of information processing agent based models. The theoretical basis is Probability theory, Statistical Mechanics, Information Theory and Machine Learning. The methods include analytical and computational techniques. The student will deal with the construction of consensus with respect to opinions on certain sets of issues and the dynamics of opinions. He will work with mathematical models and compare theoretical predictions for model societies with large ethnographic data banks. An example of a specific application to be dealt with is studying the interaction of the social hierarchical organization and the use of universal means of exchange, which is of the emergence of money.