The model explores how two types of information - social (in the form of pheromone trails) and private (in the form of route memories) affect ant colony level foraging in a variable enviroment.

Large-scale land acquisitions (LSLAs) threaten smallholder livelihoods globally. Despite more than a decade of research on the LSLA phenomenon, it remains a challenge to identify governance conditions that may foster beneficial outcomes for both smallholders and investors. One potentially promising strategy toward this end is contract farming (CF), which more directly involves smallholder households in commodity production than conditions of acquisition and displacement.

To improve understanding of how CF may mediate the outcomes of LSLAs, we developed an agent-based model of smallholder livelihoods, which we used as a virtual laboratory to experiment on a range of hypothetical LSLA and CF implementation scenarios.

The model represents a community of smallholder households in a mixed crop-livestock system. Each agent farms their own land and manages a herd of livestock. Agents can also engage in off-farm employment, for which they earn a fixed wage and compete for a limited number of jobs. The principal model outputs include measures of household food security (representing access to a single, staple food crop) and agricultural production (of a single, staple food crop).

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MOOvPOP is designed to simulate population dynamics (abundance, sex-age composition and distribution in the landscape) of white-tailed deer (Odocoileus virginianus) for a selected sampling region.

A simple model of random encounters of materials that produces distributions as found in the archaeological record.

The intention of this model is to create an universal basis on how to model change in value prioritizations within social simulation. This model illustrates the designing of heterogeneous populations within agent-based social simulations by equipping agents with Dynamic Value-based Cognitive Architectures (DVCA-model). The DVCA-model uses the psychological theories on values by Schwartz (2012) and character traits by McCrae and Costa (2008) to create an unique trait- and value prioritization system for each individual. Furthermore, the DVCA-model simulates the impact of both social persuasion and life-events (e.g. information, experience) on the value systems of individuals by introducing the innovative concept of perception thermometers. Perception thermometers, controlled by the character traits, operate as buffers between the internal value prioritizations of agents and their external interactions. By introducing the concept of perception thermometers, the DVCA-model allows to study the dynamics of individual value prioritizations under a variety of internal and external perturbations over extensive time periods. Possible applications are the use of the DVCA-model within artificial sociality, opinion dynamics, social learning modelling, behavior selection algorithms and social-economic modelling.

An agent-based model is used to simulate legislators’ behavior under secret voting rules, as influenced by the power of the accused politician, the composition of the voting body, and the publicity of the accusations.

This model is a tool to support water management on Samambaia Basin. On it you can explore different scenarios of policy, management and externalities that could influence the water uses. (Scenarios already tested include less rain and payment on water use)

This code can be used to analyze the sensitivity of the Deffuant model to different measurement errors. Specifically to:
- Intrinsic stochastic error
- Binning of the measurement scale
- Random measurement noise
- Psychometric distortions

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The purpose of this model is to explore the impact of combining archaeological palimpsests with different methods of cultural transmission on the visibility of prehistoric social networks. Up until recently, Paleolithic archaeologists have relied on stylistic similarities of artifacts to reconstruct social networks. However, this method - which is successfully applied to more recent ceramic assemblages - may not be applicable to Paleolithic assemblages, as several of those consist of palimpsests of occupations. Therefore, this model was created to study how palimpsests of occupation affect our social network reconstructions.

The model simplifies inter-groups interactions between populations who share cultural traits as they produce artifacts. It creates a proxy archaeological record of artifacts with stylistic traits that can then be used to reconstruct interactions. One can thus use this model to compare the networks reconstructed through stylistic similarities with direct contact.

Agent-Based Computational Model of the cryptocurrency Bitcoin with a realistic market and transaction system. Bitcoin’s transaction limit (i.e. block size) and Bitcoin generation can be calibrated and optimized for wealth and network’s hashing power by the Non-Dominated Sorted Genetic Algorithm - II.