The CONSERVAT model evaluates the effect of social influence among farmers in the Lake Naivasha basin (Kenya) on the spatiotemporal diffusion pattern of soil conservation effort levels and the resulting reduction in lake sedimentation.

The simulation generates two kinds of agents, whose proposals are generated accordingly to their selfish or selfless behaviour. Then, agents compete in order to increase their portfolio playing the ultimatum game with a random-stranger matching.

Both models simulate n-person prisoner dilemma in groups (left figure) where agents decide to C/D – using a stochastic threshold algorithm with reinforcement learning components. We model fixed (single group ABM) and dynamic groups (bad-barrels ABM). The purpose of the bad-barrels model is to assess the impact of information during meritocratic matching. In the bad-barrels model, we incorporated a multidimensional structure in which agents are also embedded in a social network (2-person PD). We modeled a random and homophilous network via a random spatial graph algorithm (right figure).

This is a NetLogo replication of the hill-climbing version of the Lansing-Kremer model of Balinese irrigation.

Model of influence of access to social information spread via social network on decisions in a two-person game.

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

First version of the model “Neminem laedere. Socially damaging behaviours and how to contain them” by Domenico Parisi and Nicola Lettieri

This is a simple model replicating Hardin’s Tragedy of the Commons using reactive agents that have psychological behavioral and social preferences.

This is a modified version (Netlogo 4.0.3) of the model in support of Erik Johnstons dissertation, programmed in Netlogo 3.1.4 (May 15th, 2007).

This is a series of simulations of binary group decisions and the outcomes applied to a generalized version of Price’s Equation for system fitness.