Computational Model Library

This repository includes an epidemic agent-based model that simulates the spread of Covid-19 epidemic. Normal.nlogo is the main file, while Exploring-zoning.nlogo and Exploring-Testing-With-Tracking.nlogo are modefied models to test the two strategies and run experiments.

Exploring Urban Shrinkage 2

njiang13 Andrew Crooks | Published Thu Jan 14 20:28:05 2021

While the world’s total urban population continues to grow, not all cities are witnessing such growth, some are actually shrinking. This shrinkage causes several problems to emerge including population loss, economic depression, vacant properties and the contraction of housing markets. Such problems challenge efforts to make cities sustainable. While there is a growing body of work on study shrinking cities, few explore such a phenomenon from the bottom up using dynamic computational models. To overcome this issue this paper presents an spatially explicit agent-based model stylized on the Detroit Tri-county area, an area witnessing shrinkage. Specifically, the model demonstrates how through the buying and selling of houses can lead to urban shrinkage from the bottom up. The model results indicate that along with the lower level housing transactions being captured, the aggregated level market conditions relating to urban shrinkage are also captured (i.e., the contraction of housing markets). As such, the paper demonstrates the potential of simulation to explore urban shrinkage and potentially offers a means to test polices to achieve urban sustainability.

TunaFisher ABM

Guus Ten Broeke | Published Wed Jan 13 11:27:36 2021

TunaFisher ABM simulates the decisions of fishing companies and fishing vessels of the Philippine tuna purse seinery operating in the Celebes and Sulu Seas.

High fishing effort remains in many of the world’s fisheries, including the Philippine tuna purse seinery, despite a variety of policies that have been implemented to reduce it. These policies have predominantly focused on models of cause and effect which ignore the possibility that the intended outcomes are altered by social behavior of autonomous agents at lower scales.

This model is a spatially explicit Agent-based Model (ABM) for the Philippine tuna purse seine fishery, specifically designed to include social behavior and to study its effects on fishing effort, fish stock and industry profit. The model includes economic and social factors of decision making by companies and fishing vessels that have been informed by interviews.

The SimPioN model aims to abstractly reproduce and experiment with the conditions under which a path-dependent process may lead to a (structural) network lock-in in interorganisational networks.

Path dependence theory is constructed around a process argumentation regarding three main elements: a situation of (at least) initially non-ergodic (unpredictable with regard to outcome) starting conditions in a social setting; these become reinforced by the workings of (at least) one positive feedback mechanism that increasingly reduces the scope of conceivable alternative choices; and that process finally results in a situation of lock-in, where any alternatives outside the already adopted options become essentially impossible or too costly to pursue despite (ostensibly) better options theoretically being available.

The purpose of SimPioN is to advance our understanding of lock-ins arising in interorganisational networks based on the network dynamics involving the mechanism of social capital. This mechanism and the lock-ins it may drive have been shown above to produce problematic consequences for firms in terms of a loss of organisational autonomy and strategic flexibility, especially in high-tech knowledge-intensive industries that rely heavily on network organising.

The purpose of the model is to generate coalition structures of different glove games, using a specially designed algorithm. The coalition structures can be are later analyzed by comparing them to core partitions of the game used. Core partitions are coalition structures where no subset of players has an incentive to form a new coalition.

The algorithm used in this model is an advancement of the algorithm found in Collins & Frydenlund (2018). It was used used to generate the results in Vernon-Bido & Collins (2021).

An agent-based model of echo chamber formation employing a Bayesian Source Credibility cognitive architecture limiting interactions to a single cascade.

Game of Thrones model

Claudine Gravel-Miguel Sean Bergin | Published Sun Jan 3 22:48:33 2021 | Last modified Sun Jan 3 22:49:39 2021

This model slowly evolves to become Westeros, with houses fighting for the thrones, and whitewalkers trying to kill all living things. You can download each version to see the evolution of the code, from the Wolf Sheep Predation model to the Game of Thrones model. If you are only interested in the end product, simply download the latest version.

For instructions on each step, see: https://claudinegravelmigu.wixsite.com/got-abm

Ger Grouper

Stefani Crabtree | Published Tue Jan 5 18:35:05 2021

A “Ger” is a yurt style house used by pastoralists in Mongolia. This model simulates seasonal movements, fission/fusion dynamics, social interaction between households and how these relate to climate impacts.

AmphorABM

Stefani Crabtree | Published Tue Jan 5 18:07:20 2021

This model examines the economic interaction between Gaulish wheat farmers and Etruscan and Greek wine farming in 7th century B.C. France.

The Retail Competition Agent-based Model (RC-ABM) is designed to simulate the retail competition system in the Region of Waterloo, Ontario, Canada, which which explicitly represents store competition behaviour. Through the RC-ABM, we aim to answer 4 research questions: 1) What is the level of correspondence between market share and revenue acquisition for an agent-based approach compared to a traditional location-allocation-based approach? 2) To what degree can the observed store spatial pattern be reproduced by competition? 3) To what degree are their path dependent patterns of retail success? 4) What is the relationship between retail survival and the endogenous geographic characteristics of stores and consumer expenditures?

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