My main research interests are the theoretical and experimental analysis of the dynamics of social networks, in relation to problems of cooperation and conflict.

Currently working on agent-based modeling of wealth and income distributions; formalizing some of Luhmann’s theories of communication; modeling social norms; and modeling generative mechanisms of status hierarchies.

As a Program Associate in the Research Competitiveness Program, I work on a diverse portfolio of science and technology based development projects. These projects frequently involve managing peer-review processes for grant competitions and other research and development activities as well as producing their associated progress reports. Projects are often associated with the regional and national development plans of various governments and institutions both domestic and international.

As a Master’s Thesis student, I am intended to apply Artificial Intelligence to an already existing model with the aim of making it more accurate.

Even though I do not have the focus point and the scope of the research clear yet, the road map is set to start from a very simple model to validate the technology and methodology used and then continue with more abitiuos projects.

I like the co-operation that I have found in this space and I think that I could both learn a lot from the community and add value with my novel trials and findings.

Of course I would be pleased to update the status of my project and I would try to help if I have the proper knowledge or different angle to other peers who seek for seconds opinions.

Thank you,
Francisco

I specialize in writing agent-based models for both research in and the teaching of subjects including: biology, genetics, evolution, demography, and behavior.

For my dissertation research, I have produced “B3GET,” an agent-based model which simulates populations of virtual organisms evolving over generations, whose evolutionary outcomes reflect the selection pressures of their environment. The model simulates several factors considered important in biology, including life history trade-offs, investment in body size, variation in aggression, sperm competition, infanticide, and competition over access to food and mates. B3GET calculates each agent’s ‘decision-vectors’ from its diploid chromosomes and current environmental context. These decision-vectors dictate movement, body growth, desire to mate and eat, and other agent actions. Chromosomes are modified during recombination and mutation, resulting in behavioral strategies that evolve over generations. Rather than impose model parameters based on a priori assumptions, I have used an experimental evolution procedure to evolve traits that enabled populations to persist. Seeding a succession of populations with the longest surviving genotype from each run resulted in the evolution of populations that persisted indefinitely. I designed B3GET for my dissertation, but it has an indefinite number of applications for other projects in biology. B3GET helps answer fundamental questions in evolutionary biology by offering users a virtual field site to precisely track the evolution of organismal populations. Researchers can use B3GET to: (1) investigate how populations vary in response to ecological pressures; (2) trace evolutionary histories over indefinite time scales and generations; (3) track an individual for every moment of their life from conception to post-mortem decay; and (4) create virtual analogues of living species, including primates like baboons and chimpanzees, to answer species-specific questions. Users are able to save, edit, and import population and genotype files, offering an array of possibilities for creating controlled biological experiments.