| Grant number: | 13/17131-0 |
| Support Opportunities: | Regular Research Grants |
| Start date: | December 01, 2013 |
| End date: | November 30, 2015 |
| Field of knowledge: | Physical Sciences and Mathematics - Physics |
| Principal Investigator: | José Fernando Fontanari |
| Grantee: | José Fernando Fontanari |
| Host Institution: | Instituto de Física de São Carlos (IFSC). Universidade de São Paulo (USP). São Carlos , SP, Brazil |
Abstract
An important feature of Axelrod's model of cultural dissemination is the existence of absorbing configurations that exhibit several cultural domains, despite the model's interaction rule that increases the similarity of the agents. The agents are fixed in the sites of a square lattice with nearest neighbors interactions only and are represented by a list of F cultural traits, each of which taking on an integer value among q possibilities. Depending on the values of these parameters, the steady state may or may not exhibit cultural coexistence and these two regimes are separated by a non-equilibrium phase transition in the plane (q,F). The probability that two neighboring agents interact increases with their cultural overlap: similar agents interact more frequently whereas agents that have no cultural trait in common do not interact. Our first goal is to characterize the non-equilibrium phase transition of Axelrod's model, recalling that there exist an infinite number of absorbing configurations in the thermodynamic limit and that the dynamics always freezes into one of these configurations. Our second goal is to investigate the process of diffusion of innovations by introducing a local external field that will play the role of the innovation agent. In addition, we will study the effect of demographic expansion by allowing the agents to move in the lattice. Finally, our third goal is to explore the idea of the society as a collective brain capable of carrying out complex tasks. In this case, the set of cultural traits of an agent is interpreted as a tentative solution to some optimization problem. (AU)
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