Computational Model Library

Displaying 10 of 1154 results for "Ian M Hamilton" clear search

Peer reviewed Hydroman

Dean Massey Moira Zellner | Published Saturday, May 16, 2020

Hydroman is a flexible spatially explicit model coupling human and hydrological processes to explore shallow water tables and land cover interactions in flat agricultural landscapes, modeled after the Argentine Pampas. Hydroman aligned well with established hydrological models, and was validated with water table patterns and crop yield observed in the study area.

This model analyzes two investors forming their expectations with heterogeneous strategies in order to optimize their portfolios by means of a Sharpe ratio maximization. Traders are distinguished according to their methodology used in forecasting. Two acknowledged algorithms of technical analysis have been implemented to compare portfolios performances and assess profitability of each technique.

Patch choice model from Optimal Foraging Theory (Human Behavioral Ecology)

C Michael Barton | Published Saturday, November 22, 2008 | Last modified Saturday, April 27, 2013

NetLogo model of patch choice model from optimal foraging theory (human behavioral ecology).

Consumats on a network

Marco Janssen | Published Tuesday, January 14, 2020 | Last modified Tuesday, May 30, 2023

Consumer agents make choices which products to choose using the consumat approach. In this approach agents will make choices using deliberation, repetition, imitation or social comparison dependent on the level of need satisfaction and uncertainty.
The model is discussed in Introduction to Agent-Based Modeling by Marco Janssen. For more information see https://intro2abm.com/

Modeling Arabian Upraise, a System Dynamics Approach: Egypt case study

Morteza Nazari | Published Wednesday, October 05, 2011 | Last modified Saturday, April 27, 2013

A System Dynamics Model to anticipate insurgent movements and policy design to handle them .

Change and Senescence

André Martins | Published Tuesday, November 10, 2020

Agers and non-agers agent compete over a spatial landscape. When two agents occupy the same grid, who will survive is decided by a random draw where chances of survival are proportional to fitness. Agents have offspring each time step who are born at a distance b from the parent agent and the offpring inherits their genetic fitness plus a random term. Genetic fitness decreases with time, representing environmental change but effective non-inheritable fitness can increase as animals learn and get bigger.

SEDIBASES

Sebastian Rasch | Published Monday, October 20, 2014

The Sediba socio-ecolgoical rangeland model is an biomass growth model coupled with a social model of pastoralist behaviour in a commmon pool resource setting. The social subsystem is an empircal ABM.

AMMA: Agent-based Model of the Media Arena

Annie Waldherr | Published Tuesday, February 11, 2014

The AMMA simulates how news waves emerge in the mass media. Drawing on the ideas of public arena models and issue-attention cycles, it represents fundamental principles of public communication in a virtual media system.

A flexible framework for Agent-Based Models (ABM), the ‘epiworldR’ package provides methods for prototyping disease outbreaks and transmission models using a ‘C++’ backend, making it very fast. It supports multiple epidemiological models, including the Susceptible-Infected-Susceptible (SIS), Susceptible-Infected-Removed (SIR), Susceptible-Exposed-Infected-Removed (SEIR), and others, involving arbitrary mitigation policies and multiple-disease models. Users can specify infectiousness/susceptibility rates as a function of agents’ features, providing great complexity for the model dynamics. Furthermore, ‘epiworldR’ is ideal for simulation studies featuring large populations.

Displaying 10 of 1154 results for "Ian M Hamilton" clear search

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