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.

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 system that receives from an agent-based social simulation the agent’s emotional data, their emotional-related data such as motivations and beliefs, as well as their location, and visualizes of all this information in a two dimensional map of the geographic region the agents inhabit as well as on graphs along the time dimension.

This models simulates innovation diffusion curves and it tests the effects of the degree and the direction of social influences. This model replicates, extends and departs from classical percolation models.

A friendship game is a kind of network game: a game theory model on a network. This is a NetLogo model of an agent-based adaptation of “‘Friendship-based’ Games” by PJ Lamberson. The agents reach an equilibrium that depends on the strategy played and the topology of the network.

This model simulates diffusion curves and it allows to test how social influence, network structure and consumer heterogeneity affect their spreads and their speeds.

This model is intended to explore the effectiveness of different courses of interventions on an abstract population of infections. Illustrative findings highlight the importance of the mechanisms for variability and mutation on the effectiveness of different interventions.

This model is an agent-based simulation that consists of agents who play the spatial prisioner’s dilemma game with coalition formation. The coalition dynamics are mainly influenced by how much the agents trust their leaders. The main objective is provide a simulation model to enable the analysis of the impacts that the use of trust may cause in coalition formation.

The agent based model matches origins and destinations using employment search methods at the individual level.

The core algorithm is an agent-based model, which simulates travel patterns on a network based on microscopic decision-making by each traveler.