Computational Model Library

Displaying 10 of 969 results for "J Van Der Beek" clear search

Tail biting behaviour in pigs

Iris J.M.M. Boumans Iris Jmm Boumans | Published Friday, April 22, 2016 | Last modified Wednesday, September 14, 2016

The model simulates tail biting behaviour in pigs and how they can turn into a biter and/or victim. The effect of a redirected motivation, behavioural changes in victims and preference to bite a lying pig on tail biting can be tested in the model

John Q. Public (JQP): A Model of Political Judgment and Behavior

Sung-Youn Kim | Published Monday, March 14, 2011 | Last modified Saturday, April 27, 2013

The model integrates major theories of political judgment and behavior within the classical cognitive paradigm embedded in the ACT-R cognitive architecture. It models preferences and beliefs of political candidates, parties, and groups.

Feedback Loop Example: Wildland Fire Spread

James Millington | Published Friday, December 21, 2012 | Last modified Saturday, April 27, 2013

This model is a replication of that described by Peterson (2002) and illustrates the ‘spread’ feedback loop type described in Millington (2013).

The Cardial Spread Model

Sean Bergin | Published Friday, September 29, 2017 | Last modified Monday, February 04, 2019

The purpose of this model is to provide a platform to test and compare four conceptual models have been proposed to explain the spread of the Impresso-Cardial Neolithic in the west Mediterranean.

This is a simulation of an insurance market where the premium moves according to the balance between supply and demand. In this model, insurers set their supply with the aim of maximising their expected utility gain while operating under imperfect information about both customer demand and underlying risk distributions.

There are seven types of insurer strategies. One type follows a rational strategy within the bounds of imperfect information. The other six types also seek to maximise their utility gain, but base their market expectations on a chartist strategy. Under this strategy, market premium is extrapolated from trends based on past insurance prices. This is subdivided according to whether the insurer is trend following or a contrarian (counter-trend), and further depending on whether the trend is estimated from short-term, medium-term, or long-term data.

Customers are modelled as a whole and allocated between insurers according to available supply. Customer demand is calculated according to a logit choice model based on the expected utility gain of purchasing insurance for an average customer versus the expected utility gain of non-purchase.

Within the archeological record for Bronze Age Chinese culture, there continues to be a gap in our understanding of the sudden rise of the Erlitou State from the previous late Longshan chiefdoms. In order to examine this period, I developed and used an agent-based model (ABM) to explore possible socio-politically relevant hypotheses for the gap between the demise of the late Longshan cultures and rise of the first state level society in East Asia. I tested land use strategy making and collective action in response to drought and flooding scenarios, the two plausible environmental hazards at that time. The model results show cases of emergent behavior where an increase in social complexity could have been experienced if a catastrophic event occurred while the population was sufficiently prepared for a different catastrophe, suggesting a plausible lead for future research into determining the life of the time period.

The ABM published here was originally developed in 2016 and its results published in the Proceedings of the 2017 Winter Simulation Conference.

Informal risk-sharing cooperatives : ORP and Learning

Juliette Rouchier Victorien Barbet Renaud Bourlès | Published Monday, February 13, 2017 | Last modified Tuesday, May 16, 2023

The model studies the dynamics of risk-sharing cooperatives among heterogeneous farmers. Based on their knowledge on their risk exposure and the performance of the cooperative farmers choose whether or not to remain in the risk-sharing agreement.

{LogoClim}: WorldClim in NetLogo

Leandro Garcia Daniel Vartanian Aline Martins de Carvalho Aline | Published Thursday, July 03, 2025 | Last modified Monday, August 04, 2025

LogoClim is a NetLogo model for simulating and visualizing global climate conditions. It allows researchers to integrate high-resolution climate data into agent-based models, supporting reproducible research in ecology, agriculture, environmental science, and other fields that rely on climate data integration.

The model utilizes raster data to represent climate variables such as temperature and precipitation over time. It incorporates historical data (1951-2024) and future climate projections (2021-2100) derived from global climate models under various Shared Socioeconomic Pathways (SSPs) (O’Neill et al., 2017). All climate inputs come from WorldClim 2.1, a widely used source of high-resolution, interpolated climate datasets based on weather station observations worldwide (Fick & Hijmans, 2017), available for academic and other non-commercial use.

See the Logônia model for an example of how to integrate LogoClim into your model.

We model the relationship between natural resource user´s individual time preferences and their use of destructive extraction method in the context of small-scale fisheries.

A test-bed ecological model

Bruce Edmonds | Published Sunday, May 04, 2014 | Last modified Wednesday, May 15, 2019

This is a multi-patch meta-population ecological model. It intended as a test-bed in which to test the impact of humans with different kinds of social structure.

Displaying 10 of 969 results for "J Van Der Beek" clear search

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