Wednesday, March 22, 2017

Humans of Simulated New York: comprehensive ABM model of city life

Here is a very interesting project that aims towards building agent based models to simulate cities and the impacts of policies on them. The project is available on GitHub. Kudos to the authors, who are all on Twitter btw Francis TsengFei Liu and Bernardo Furtado.

Tseng, F., Liu, F., & Furtado, B. A. (2017). Humans of Simulated New York (HOSNY): an exploratory comprehensive model of city life. arXiv preprint arXiv:1703.05240.

The model presented in this paper experiments with a comprehensive simulant agent in order to provide an exploratory platform in which simulation modelers may try alternative scenarios and participation in policy decision-making. The framework is built in a computationally distributed online format in which users can join in and visually explore the results. Modeled activity involves daily routine errands, such as shopping, visiting the doctor or engaging in the labor market. Further, agents make everyday decisions based on individual behavioral attributes and minimal requirements, according to social and contagion networks. Fully developed firms and governments are also included in the model allowing for taxes collection, production decisions, bankruptcy and change in ownership. The contributions to the literature are multifold. They include (a) a comprehensive model with detailing of the agents and firms' activities and processes and original use of simultaneously (b) reinforcement learning for firm pricing and demand allocation; (c) social contagion for disease spreading and social network for hiring opportunities; and (d) Bayesian networks for demographic-like generation of agents. All of that within a (e) visually rich environment and multiple use of databases. Hence, the model provides a comprehensive framework from where interactions among citizens, firms and governments can be easily explored allowing for learning and visualization of policies and scenarios.

credit: Francis Tseng

No comments: