Work in the area of complex adaptive systems is in progress. This goes from analysing a very simple society, used to model artificial societies. The main subject has been "Cooperation", and we studied a model using the Prisoners Dilemma in a random network. We have studied how cooperation can arise whenever agents are allowed to change partners, thus the network of connections was allowed to evolve.
Also another application of evolving networks is that of a finantial market model. We have studied how the herding effect may account part of the large probability of large returns in a stock value. The model is an evolving percolation type model, which may be interesting for other applications as well.
I am currently interested in stochastic system. What are the tools to understand the dynamics of a stochastic system? Stationary probability distributions are clearly not enough to recover dynamics. How can we extract dynamical information out of a stochastic system? We have modeled spatio-temporal intermittency via a stochastic extended system. Our main contribution was to show how the nucleation of a metastable state may develop as spatio-temporal intermittency.
Check out my list publications and preprints
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