We present an agent-based model that maps out and simulates the processes by which individuals within ecological restoration organizations communicate and collectively make restoration decisions.

The DITCH model has been developed to investigate partner selection processes, focusing on individual preferences, opportunities for contact, and group size to uncover how these may lead to differential rates of inter-­ethnic marriage.

This model simulates the mechanisms of evolution, or how allele frequencies change in a population over time.

In this model agents meet, evaluate one another, decide whether or not to date, if and when to become sexual partners, and when to break up.

A very simple model elaborated to explore what may happens when buyers (travelers) have more information than sellers (tourist destinations)

This spatially explicit agent-based model addresses how effective foraging radius (r_e) affects the effective size–and thus the equilibrium cultural diversity–of a structured population composed of central-place foraging groups.

The model measures drivers of effectiveness of risk assessments in risk workshops regarding the correctness and required time. Specifically, we model the limits to information transfer, incomplete discussions, group characteristics, and interaction patterns and investigate their effect on risk assessment in risk workshops.

The model simulates a discussion in the context of a risk workshop with 9 participants. The participants use Bayesian networks to assess a given risk individually and as a group.

An agent-based model simulating West Nile Virus dynamics in a one host (American robin)-one vector (Culex spp. mosquito) system. ODD improved and code cleaned.

An ABM, derived from a case study and a series of surveys with greenhouse growers in the Westland, Netherlands. Experiments using this model showshow that the greenhouse horticulture industry displays diversity, adaptive complexity and an uneven distribution, which all suggest that the industry is an evolving system.

The Communicating Hazard Information in the Modern Environment (CHIME) agent-based model (ABM) is a Netlogo program that facilitates the analysis of information flow and protective decisions across space and time during hazardous weather events. CHIME ABM provides a platform for testing hypotheses about collective human responses to weather forecasts and information flow, using empirical data from historical hurricanes. The model uses real world geographical and hurricane data to set the boundaries of the simulation, and it uses historical hurricane forecast information from the National Hurricane Center to initiate forecast information flow to citizen agents in the model.