This model has been created with and for the researcher-farmers of the Muonde Trust (http://www.muonde.org/), a registered Zimbabwean non-governmental organization dedicated to fostering indigenous innovation. Model behaviors and parameters (mashandiro nemisiyano nedzimwe model) derive from a combination of literature review and the collected datasets from Muonde’s long-term (over 30 years) community-based research. The goals of this model are three-fold (muzvikamu zvitatu):
A) To represent three components of a Zimbabwean agro-pastoral system (crops, woodland grazing area, and livestock) along with their key interactions and feedbacks and some of the human management decisions that may affect these components and their interactions.
B) To assess how climate variation (implemented in several different ways) and human management may affect the sustainability of the system as measured by the continued provisioning of crops, livestock, and woodland grazing area.
C) To provide a discussion tool for the community and local leaders to explore different management strategies for the agro-pastoral system (hwaro/nzira yekudyidzana kwavanhu, zvipfuo nezvirimwa), particularly in the face of climate change.

This program was developed to simulate monogamous reproduction in small populations (and the enforcement of the incest taboo).

Every tick is a year. Adults can look for a mate and enter a relationship. Adult females in a Relationship (under the age of 52) have a chance to become pregnant. Everyone becomes not alive at 77 (at which point people are instead displayed as flowers).

User can select a starting-population. The starting population will be adults between the ages of 18 and 42.

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Evolution of Sex is a NetLogo model that illustrates the advantages and disadvantages of sexual and asexual reproductive strategies. It seeks to demonstrate the answer to the question “Why do we have sex?”

This is a replication model of the matching problem including the mate search problem, which is the generalization of a traditional optimization problem.

Models land-use, perception, and biocultural interactions between two forager populations.

Simulates biobehavioral interactions between 2 populations of hominins.

The simulation model conducts fine-grained population projection by specifying life course dynamics of individuals and couples by means of traditional demographic microsimulation and by using agent-based modeling for mate matching.

This model is an extended version of the matching problem including the mate search problem, which is the generalization of a traditional optimization problem. The matching problem is extended to a form of asymmetric two-sided matching problem.

A general model of human mate choice in which agents are localized in space, interact with close neighbors, and tend to range either near or far. At the individual level, our model uses two oft-used but incompletely understood decision rules: one based on preferences for similar partners, the other for maximally attractive partners.