The NIER model is intended to add qualitative variables of building owner types and peer group scales to existing energy efficiency retrofit adoption models. The model was developed through a combined methodology with qualitative research, which included interviews with key stakeholders in Cleveland, Ohio and Detroit and Grand Rapids, Michigan. The concepts that the NIER model adds to traditional economic feasibility studies of energy retrofit decision-making are differences in building owner types (reflecting strategies for managing buildings) and peer group scale (neighborhoods of various sizes and large-scale Districts). Insights from the NIER model include: large peer group comparisons can quickly raise the average energy efficiency values of Leader and Conformist building owner types, but leave Stigma-avoider owner types as unmotivated to retrofit; policy interventions such as upgrading buildings to energy-related codes at the point of sale can motivate retrofits among the lowest efficient buildings, which are predominantly represented by the Stigma-avoider type of owner; small neighborhood peer groups can successfully amplify normal retrofit incentives.

MELBIS-V1 is a spatially explicit agent-based model that allows the geospatial simulation of the decision-making process of newcomers arriving in the bilingual cities and boroughs of the island of Montreal, Quebec in CANADA, and the resulting urban segregation spatial patterns. The model was implemented in NetLogo, using geospatial raster datasets of 120m spatial resolution.

MELBIS-V2 enhances MELBIS-V1 to implement and simulate the decision-making processes of incoming immigrants, and to analyze the resulting spatial patterns of segregation as immigrants arrive and settle in various cities in Canada. The arrival and segregation of immigrants is modeled with MELBIS-V2 and compared for three major Canadian immigration gateways, including the City of Toronto, Metro Vancouver, and the City of Calgary.

The code for the paper “Social norms and the dominance of Low-doers”

We use a threshold model to drive our simulated network analysis testing public support for candidates in invisible primaries. We assign voter thresholds for candidates and vary number of voters, attachment to candidates and decay. Results of the algorithm show effects of size of lead, attachment and size of decay.

Spatial explicit model of a rangeland system, based on Australian conditions, where grass, woody shrubs and fire compete fore resources. Overgrazing can cause the system to flip from a healthy state to an unproductive shrub state. With the model one can explore the consequences of different movement rules of the livestock on the resilience of the system.

The model is discussed in Introduction to Agent-Based Modeling by Marco Janssen. For more information see https://intro2abm.com/.

This model allows for the investigation of the effect spatial clustering of raw material sources has on the outcome of the neutral model of stone raw material procurement by Brantingham (2003).

A more complete description of the model can be found in Appendix I as an ODD protocol. This model is an expansion of the Hemelrijk (1996) that was expanded to include a simple food seeking behavior.

Butterflies (turtles) goes through metamorphism and moves to corresponding patches each season of the year. The number of years and seasons are monitored.

This model is a small extension (rectangular layout) of Joshua Epstein’s (2001) model on development of thoughtless conformity in an artificial society of agents.

This is an adaptation and extension of Robert Axtell’s model (2013) of endogenous firms, in Python 3.4