The TERROIR agent-based model was built for the multi-level analysis of biomass and nutrient flows within agro-sylvo-pastoral villages in West Africa. It explicitly takes into account both human organization and spatial extension of such flows.

The aim of this model is to explore and understand the factors driving adoption of treatment strategies for ecological disturbances, considering payoff signals, learning strategies and social-ecological network structure

This is an agent-based model that simulates the structural evolution in food supply chain.

We propose an agent-based model where a fixed finite population of tagged agents play iteratively the Nash demand game in a regular lattice. The model extends the bargaining model by Axtell, Epstein and Young.

This ABM deals with commuting choices in the Italian city of Varese. Empirical data inform agents’ attitudes and modal choices costs and emissions. We evaluate ex ante the impact of policies for less polluting commuting choices.

The original Ache model is used to explore different distributions of resources on the landscape and it’s effect on optimal strategies of the camps on hunting and camp movement.

In this model, we simulate the navigation behavior of homing pigeons. Specifically we use genetic algorithms to optimize the navigation and flocking parameters of pigeon agents.

The model simulates agents in a spatial environment competing for a common resource that grows on patches. The resource is converted to energy, which is needed for performing actions and for surviving.

A NetLogo ABM developed to explore unarmed resistance to an active shooter. The landscape is a generalized open outdoor area. Parameters enable the user to set shooter armament and control for assumptions with regard to shooter accuracy.

This Repast Simphony model simulates genomic admixture during the farming expansion of human groups from mainland Asia into the Papuan dominated islands of Southeast Asia during the Neolithic period.