Computational Model Library

Displaying 10 of 133 results for "Andrew Nelson" clear search

TechNet_04: Cultural Transmission in a Spatially-Situated Network

Andrew White | Published Monday, October 08, 2012 | Last modified Saturday, April 27, 2013

The TechNet_04 is an abstract model that embeds a simple cultural tranmission process in an environment where interaction is structured by spatially-situated networks.

Stochastic vs. Deterministic Spatial PD

Andrew Bausch | Published Friday, November 01, 2013 | Last modified Monday, April 08, 2019

This model implements a Spatial Prisoner’s Dilemma with the option to change whether agents interact deterministically or stochastically.

ForagerNet3_Demography_V2

Andrew White | Published Thursday, February 13, 2014

ForagerNet3_Demography_V2 is a non-spatial ABM for exploring hunter-gatherer demography. This version (developed from FN3D_V1) contains code for calculating the ratio of old to young adults (the “OY ratio”) in the living and dead populations.

Irrigation Equity and Efficiency

Andrew Bell | Published Tuesday, August 30, 2016

The purpose of this model is to examine equity and efficiency in crop production across a system of irrigated farms, as a function of maintenance costs, assessed water fees, and the capacity of farmers to trade water rights among themselves.

Exploring Urban Shrinkage

Andrew Crooks | Published Thursday, March 19, 2020

While the world’s total urban population continues to grow, this growth is not equal. Some cities are declining, resulting in urban shrinkage which is now a global phenomenon. Many problems emerge due to urban shrinkage including population loss, economic depression, vacant properties and the contraction of housing markets. To explore this issue, this paper presents an agent-based model stylized on spatially explicit data of Detroit Tri-county area, an area witnessing urban shrinkage. Specifically, the model examines how micro-level housing trades impact urban shrinkage by capturing interactions between sellers and buyers within different sub-housing markets. The stylized model results highlight not only how we can simulate housing transactions but the aggregate market conditions relating to urban shrinkage (i.e., the contraction of housing markets). To this end, the paper demonstrates the potential of simulation to explore urban shrinkage and potentially offers a means to test polices to alleviate this issue.

Human-in-the-loop Experiment of the Strategic Coalition Formation using the glove game

Andrew Collins | Published Monday, November 23, 2020 | Last modified Wednesday, June 22, 2022

The purpose of the model is to collect information on human decision-making in the context of coalition formation games. The model uses a human-in-the-loop approach, and a single human is involved in each trial. All other agents are controlled by the ABMSCORE algorithm (Vernon-Bido and Collins 2020), which is an extension of the algorithm created by Collins and Frydenlund (2018). The glove game, a standard cooperative game, is used as the model scenario.

The intent of the game is to collection information on the human players behavior and how that compares to the computerized agents behavior. The final coalition structure of the game is compared to an ideal output (the core of the games).

MHCABM is an agent-based, multi-hazard risk interaction model with an integrated applied dynamic adaptive pathways planning component. It is designed to explore the impacts of climate change adaptation decisions on the form and function of a coastal human-environment system, using as a case study an idealised patch based representation of the Mount North-Omanu area of Tauranga city, New Zealand. The interacting hazards represented are erosion, inundation, groundwater intrusion driven by intermittent heavy rainfall / inundations (storm) impacts, and sea level rise.

A model that representa farmers potential to adopt bio-fuels in Georgia

The Agent-Based Model for Multiple Team Membership (ABMMTM) simulates design teams searching for viable design solutions, for a large design project that requires multiple design teams that are working simultaneously, under different organizational structures; specifically, the impact of multiple team membership (MTM). The key mechanism under study is how individual agent-level decision-making impacts macro-level project performance, specifically, wage cost. Each agent follows a stochastic learning approach, akin to simulated annealing or reinforcement learning, where they iteratively explore potential design solutions. The agent evaluates new solutions based on a random-walk exploration, accepting improvements while rejecting inferior designs. This iterative process simulates real-world problem-solving dynamics where designers refine solutions based on feedback.

As a proof-of-concept demonstration of assessing the macro-level effects of MTM in organizational design, we developed this agent-based simulation model which was used in a simulation experiment. The scenario is a system design project involving multiple interdependent teams of engineering designers. In this scenario, the required system design is split into three separate but interdependent systems, e.g., the design of a satellite could (trivially) be split into three components: power source, control system, and communication systems; each of three design team is in charge of a design of one of these components. A design team is responsible for ensuring its proposed component’s design meets the design requirement; they are not responsible for the design requirements of the other components. If the design of a given component does not affect the design requirements of the other components, we call this the uncoupled scenario; otherwise, it is a coupled scenario.

AMBAWA simulates the flows of biomass between crop and livestock systems at the field, farm, and village scales in order to showcase innovating management practices of soil fertility in West Africa.

Displaying 10 of 133 results for "Andrew Nelson" clear search

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