https://orcid.org/0000-0002-1524-3529
GitHub more info
PhD in anthropology by Universidad de Buenos Aires, professor in graduate and posgraduate courses and researcher in Universidad de Buenos Aires and Universidad Nacional de Lanus
Methodology, quantitative and qualitative, agent based models, social networks analysis, machine learning, AI, anthropology of the food, nutritional anthropology, health anthropology
This models simulate how people choose their food buyings based on a limited budget and a food quality index. In order to make the choice the agents call a genetic algorithm who optimizes the buying. The agents are distributed randomly and there are 5 store options where agents can buy meat, fruits and vegetables, bread, ultraprocessed and medications. Agents need all of them, each of one has a different price and a different quality index. The genetic algorithm perform an optimization procedure in order to clasiffy what food set is the best for each agent. The agents are coloured based on their budget if the’ve got less than 100, then they are pink otherwise they are white.
Under development.