The student will engage in an ongoing research program that deals with (I) learning in Neural Networks and (II) the construction and analysis of agent based models that process information using neural networks. The theoretical background includes Probability theory, Statistical Mechanics, Information theory and Machine Learning. The methods include analytical and computational techniques. Applications to consensus formation with respect to moral opinions and to the study of opinion dynamics. The student will compare machines learning with different learning algorithms e compare theoretical predictions to large data bamks about moral opinions, ethnographic data and voting patterns in legislative houses from different countries.
News published in Agência FAPESP Newsletter about the scholarship: