Computational Model Library

Displaying 10 of 107 results random clear search

Simulation Software for Random-Subset Voting with Borda, approval, plurality and Condorcet.

This software simulates the Random-Subset Voting method for Borda, plurality, approval and Condorcet.

Peer reviewed Organizational behavior in the hierarchy model

Smarzhevskiy Ivan | Published Tuesday, June 18, 2019 | Last modified Wednesday, July 31, 2019

In a two-level hierarchical structure (consisting of the positions of managers and operators), persons holding these positions have a certain performance and the value of their own (personal perception in this, simplified, version of the model) perception of each other. The value of the perception of each other by agents is defined as a random variable that has a normal distribution (distribution parameters are set by the control elements of the interface).
In the world of the model, which is the space of perceptions, agents implement two strategies: rapprochement with agents that perceive positively and distance from agents that perceive negatively (both can be implemented, one of these strategies, or neither, the other strategy, which makes the agent stationary). Strategies are implemented in relation to those agents that are in the radius of perception (PerRadius).
The manager (Head) forms a team of agents. The performance of the group (the sum of the individual productivities of subordinates, weighted by the distance from the leader) varies depending on the position of the agents in space and the values of their individual productivities. Individual productivities, in the current version of the model, are set as a random variable distributed evenly on a numerical segment from 0 to 100. The manager forms the team 1) from agents that are in (organizational) radius (Op_Radius), 2) among agents that the manager perceives positively and / or negatively (both can be implemented, one of the specified rules, or neither, which means the refusal of the command formation).
Agents can (with a certain probability, given by the variable PrbltyOfDecisn%), in case of a negative perception of the manager, leave his group permanently.
It is possible in the model to change on the fly radii values, update the perception value across the entire population and the perception of an individual agent by its neighbors within the perception radius, and the probability values for a subordinate to make a decision about leaving the group.
You can also change the set of strategies for moving agents and strategies for recruiting a team manager. It is possible to add a randomness factor to the movement of agents (Stoch_Motion_Speed, the default is set to 0, that is, there are no random movements).

MERCURY extension: population

Tom Brughmans | Published Thursday, May 23, 2019

This model is an extended version of the original MERCURY model (https://www.comses.net/codebases/4347/releases/1.1.0/ ) . It allows for experiments to be performed in which empirically informed population sizes of sites are included, that allow for the scaling of the number of tableware traders with the population of settlements, and for hypothesised production centres of four tablewares to be used in experiments.

Experiments performed with this population extension and substantive interpretations derived from them are published in:

Hanson, J.W. & T. Brughmans. In press. Settlement scale and economic networks in the Roman Empire, in T. Brughmans & A.I. Wilson (ed.) Simulating Roman Economies. Theories, Methods and Computational Models. Oxford: Oxford University Press.

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.

GRASP world

Gert Jan Hofstede | Published Tuesday, April 16, 2019

This agent-based model investigates group longevity in a population in a foundational way, using theory on social relations and culture. It is the first application of the GRASP meta-model for social agents, containing elements of Groups, Rituals, Affiliation, Status, and Power. It can be considered an exercise in artificial sociality: a culture-general, content-free base-line trust model from which to engage in more specific studies. Depending on cultural settings for individualism and power distance, as well as settings for xenophobia and for the increase of trust over group life, the GRASP world model generates a variety of patters. Number of groups ranges from one to many, composition from random to segregated, and pattern genesis from rapid to many hundreds of time steps. This makes GRASP world an instrument that plausibly models some basic elements of social structure in different societies.

NetLogo-R-Example for the Inititialisation of Agents with Correlated Random Numbers

Danilo Saft | Published Friday, February 14, 2014 | Last modified Monday, April 08, 2019

This is a short NetLogo example demonstrating how to initialize 500 agents with 4 correlated parameters each with random values by doing the necessary calculations in the program “R” and retrieving the results.

Food Safety Inspection Model - Stores Signal with Errors

Sara Mcphee-Knowles | Published Wednesday, March 05, 2014 | Last modified Monday, April 08, 2019

The Inspection Model represents a basic food safety system where inspectors, consumers and stores interact. The purpose of the model is to provide insight into an optimal level of inspectors in a food system by comparing three search strategies.

Food Safety Inspection Model - Random Strategy

Sara Mcphee-Knowles | Published Wednesday, March 05, 2014 | Last modified Monday, April 08, 2019

The Inspection Model represents a basic food safety system where inspectors, consumers and stores interact. The purpose of the model is to provide insight into an optimal level of inspectors in a food system by comparing three search strategies.

This model is an application of Brantingham’s neutral model to a real landscape with real locations of potential sources. The sources are represented as their sizes during current conditions, and from marine geophysics surveys, and the agent starts at a random location in Mossel Bay Region (MBR) surrounding the Archaeological Pinnacle Point (PP) locality, Western Cape, South Africa. The agent moves at random on the landscape, picks up and discards raw materials based only upon space in toolkit and probability of discard. If the agent happens to encounter the PP locality while moving at random the agent may discard raw materials at it based on the discard probability.

Displaying 10 of 107 results random clear search

This website uses cookies and Google Analytics to help us track user engagement and improve our site. If you'd like to know more information about what data we collect and why, please see our data privacy policy. If you continue to use this site, you consent to our use of cookies.
Accept