I study human culture and cooperation in relationship to the environment. In particular, I study how social norms, institutions and societies evolve, and how they are influenced by ecological and social forces. I strive to use this research to learn how to better build durable, sustainable and just institutions and societies. I use experimental economics and agent-based modeling to explore these connections, and work with lot of wonderful people.

Application of complexity science and organizational culture to healthcare performance

Didier’s Research:
are related to interoperability and conflation models in geospatial analysis and integrated modelling applications, particularly in the context of spatial data infrastructures such as GEOSS. This translates to a focus on geospatial statistics, geospatial patterns, outbreak detection and geospatial data mining in general, but also to data quality and uncertainty propagation principles in relation to geoworkflows connected to/using web services. Didier’s research centres on environmental agro-ecological geospatial models, and public health and spatial epidemiology applications. (see website)

Jorge is a PhD candidate of System Design Engineering at the University of Waterloo. His research activities are focused on applying agent-based models on three major areas: 1) financial markets to study the self-regulation capability of artificial markets with interacting investors and credit rating agencies; 2) the efficiency of road networks when users have access to real-time information and are able to adjust their behavior to current conditions; 3) failure probability of nuclear waste containers due to microbial- and chemical-driven corrosion.

My profound interest in networks convinced me to work in these subjects and start my master project on an application of social network analysis for detecting organized fraud in Automobile insurance, which helps to flag groups of fraudsters. The key point of this project is simply to find fraudulent rings, while the most of traditional methods have only taken opportunistic fraud into consideration. My duty in research is to design an algorithm for identifying cyclic components, then to be compared with theoretical ones. This project showed me how networks are used in the analysis of relations.

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 am a spatial (GIS) agent-based modeler i.e. modeler that simulates the impact of various individual decisions on the environment. My work is mainly methodological i.e. I develop tools that make agent-based modeling (ABM) easier to do. I especially focus on developing tools that allow for evaluating various uncertainties in ABM. One of these uncertainties are the ways of quantifying agent decisions (i.e. the algorithmic representation of agent decision rules) for example to address the question of “How do the agents decide whether to grow crops or rather put land to fallow?”. One of the methods I developed focuses on representing residential developers’ risk perception for example to answer the question: “to what extent is the developer risk-taking and would be willing to build new houses targeted at high-income families (small market but big return on investment)?”. Other ABM uncertainties that I evaluate are various spatial inputs (e.g. different representations of soil erosion, different maps of environmental benefits from land conservation) and various demographics (i.e. are retired farmers more willing to put land to conservation?). The tools I develop are mostly used in (spatial) sensitivity analysis of ABM (quantitative, qualitative, and visual).

Applications of agent-based modeling and complexity theory to real-world problems. I am particular interested in stigmergic polyagents, their relation to the path integral formalization of quantum physics, and their application to combinatorially explosive problems, but also work extensively in modeling social systems.

My research centers on isolating how and to what extent political institutions themselves shape policy. I use computational modeling (agent-based and simulation) to gain theoretical leverage on the issue. This approach allows me to place groups of actors with given preferences into different institutional settings in order to gauge the effect of the rules of the game on political outcomes. Most of my research examines the ways in which legislative processes affect issues of political economy, such as income redistribution.