Indirect reciprocity can be evolved by the shared information among the people of small subgroups in the population.

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

A hybrid predator-prey model of fish and plankton that switches dynamically between ABM and SD representations. It contains 6 related structural designs of the same model.

This is a model of a community of online communities. Using mechanisms such as win-stay, lose-shift, and preferential attachment the model can reproduce similar patterns to those of the Stack Exchange network.

This model converts cleaned up versions of .pgn files (records of real chess games) and conversts them into files that record all of the events and “possible” events within a game of chess. This is intended to be a way to create sets of data that capture event sequences within the relatively complex but finite context of chess games as a proxy or “toy” data set. Although not a perfect correlation, these toy data sets are a first step in analysing complex and dynamic systems of events and possible events that happen in the real world.

This model takes into consideration Peer Reviewing under the influence of Impact Factor (PRIF) and it has the purpose to explore whether the infamous metric affects assessment of papers under review. The idea is to consider to types of reviewers, those who are agnostic towards IF (IU1) and those that believe that it is a measure of journal (and article) quality (IU2). This perception is somehow reflected in the evaluation, because the perceived scientific value of a paper becomes a function of the journal in which an article has been submitted. Various mechanisms to update reviewer preferences are also implemented.

Although beneficial to scientific development, data sharing is still uncommon in many research areas. Various organisations, including funding agencies that endorse open science, aim to increase its uptake. However, estimating the large-scale implications of different policy interventions on data sharing by funding agencies, especially in the context of intense competition among academics, is difficult empirically. Here, we built an agent-based model to simulate the effect of different funding schemes (i.e., highly competitive large grants vs. distributive small grants), and varying intensity of incentives for data sharing on the uptake of data sharing by academic teams strategically adapting to the context.

This NetLogo model represents hunters and forestry road development in a spatial landscape. The cumulative effects of multiple resource use is explored.

This model contains source code and a technical appendix for the paper “Effects of Resource Availability on Consensus Decision Making in Primates”.

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