A logging agent builds roads based on the location of high-value hotspots, and cuts trees based on road access. A forest monitor sanctions the logger on observed infractions, reshaping the pattern of road development.

An individual-based model to evaluate, whether time delays in plant responses to insect herbivory can be beneficial for the plant.

The model explores the impact of journal metrics (e.g., the notorious impact factor) on the perception that academics have of an article’s scientific value.

CRESY-I stands for CREativity from a SYstems perspetive, Model I. This is the base model in a series designed to describe a systems approach to creativity in terms of variation, selection and retention (VSR) subprocesses.

The set of models test how receivers ability to accurately rank signalers under various ecological and behavioral contexts.

This model employs optimal foraging theory principles to generate predictions of which coastal habitats are exploited in climatically stable versus variable environments, using the American Samoa as a study area.

This is a computational model to articulate the theory and test some assumption and axioms for the trust model and its relationship to SBH.

This is a very simple foraging model used to illustrate the features of Netlogo’s Profiler extension.

A discrete-time stochastic model with state-dependent transmission probabilities and multi-agent simulations focusing on possible risks that could materialize in the final phase of the epidemic.

An empirically validated agent-based model of circular migration