Computational Model Library

A Model to Unravel the Complexity of Rural Food Security

Samantha Dobbie Stefano Balbi | Published Mon Aug 22 12:04:04 2016 | Last modified Sun Dec 2 04:27:46 2018

An ABM to simulate the behaviour of households within a village and observe the emerging properties of the system in terms of food security. The model quantifies food availability, access, utilisation and stability.

This program simulates a group of hunter-gatherer (households) moving randomly over an artificial landscapoe pulated with resources randomly distributed (a Gaussian distribution). To survive, agents hunt and gather using their own labor resources and available technology. When labor and technology is not enough to compensate the resource difficulty of access, they need to cooperate. The purpose of the model is to analyze the consequences of cooperation on cultural diversity: the more the agents cooperate, the more their culture (a 10 componenet vector) is updated to imitate the culture of cooperative agents. The less the agent cooperates, the more different its culture becomes.

The model simulates seven agents engaging in collective action and inter-network social learning. The objective of the model is to demonstrate how mental models of agents can co-evolve through a complex relationship among factors influencing decision-making, such as access to knowledge and personal- and group-level constraints.

Peer reviewed Agent-based Renewables model for Integrated Sustainable Energy (ARISE)

Muhammad Indra Al Irsyad Anthony Halog Rabindra Nepal | Published Wed Nov 29 00:55:57 2017 | Last modified Fri Oct 5 01:16:27 2018

ARISE is a hybrid energy model incorporating macroeconomic data, micro socio-economic data, engineering data and environmental data. This version of ARISE can simulate scenarios of solar energy policy for Indonesia case.

Network structures tutorial

Tom Brughmans | Published Sun Sep 30 08:32:57 2018 | Last modified Tue Oct 2 09:48:18 2018

A draft model with some useful code for creating different network structures using the Netlogo NW extension. This model is used for the following tutorial:
Brughmans, T. (2018). Network structures and assembling code in Netlogo, Tutorial, https://archaeologicalnetworks.wordpress.com/resources/#structures .

Importing a Roman transport network

Tom Brughmans | Published Sun Sep 30 08:50:43 2018

A draft model teaching how a Roman transport model can be imported into Netlogo, and the issues confronted when importing and reusing open access Roman datasets. This model is used for the tutorial:
Brughmans, T. (2018). Importing a Roman Transport network with Netlogo, Tutorial, https://archaeologicalnetworks.wordpress.com/resources/#transport .

Project for the course “Introduction to Agent-Based Modeling”.

The NetLogo model implements an Opinion Dynamics model with different confidence distributions, inspired by the Bounded Confidence model presented by Hegselmann and Krause in 2002. Hegselmann and Krause used a model with uniform distribution of confidence, but one could imagine agents that are more confident in their own opinions than others. Confidence with triangular, semi-circular, and Gaussian distributions are implemented. Moreover, network structure is optional and can be taken into account in the agent’s confidence such that agents assign less confidence the further away from them other agents are.

Peer reviewed The emergence of tag-mediated altruism in structured societies

Shade Shutters David Hales | Published Tue Jan 20 21:36:12 2015 | Last modified Mon Jun 1 20:13:51 2015

This abstract model explores the emergence of altruistic behavior in networked societies. The model allows users to experiment with a number of population-level parameters to better understand what conditions contribute to the emergence of altruism.

Peer reviewed Emergent Firms Model

J Applegate | Published Fri Jul 13 15:04:37 2018

The Emergent Firm (EF) model is based on the premise that firms arise out of individuals choosing to work together to advantage themselves of the benefits of returns-to-scale and coordination. The Emergent Firm (EF) model is a new implementation and extension of Rob Axtell’s Endogenous Dynamics of Multi-Agent Firms model. Like the Axtell model, the EF model describes how economies, composed of firms, form and evolve out of the utility maximizing activity on the part of individual agents. The EF model includes a cash-in-advance constraint on agents changing employment, as well as a universal credit-creating lender to explore how costs and access to capital affect the emergent economy and its macroeconomic characteristics such as firm size distributions, wealth, debt, wages and productivity.

A series of studies show the applicability of the NK model in the crowdsourcing research, but it also exposes a problem that the application of the NK model is not tightly integrated with crowdsourcing process, which leads to lack of a basic crowdsourcing simulation model. Accordingly, by introducing interaction relationship among task decisions to define three tasks of different structure: local task, small-world task and random task, and introducing bounded rationality and its two dimensions are taken into account: bounded rationality level that used to distinguish industry types and bounded rationality bias that used to differentiate professional users and ordinary users, an agent-based model that simulates the problem-solving process of tournament-based crowdsourcing is constructed by combining the NK fitness landscapes and the crowdsourcing framework of “Task-Crowd-Process-Evaluation”.

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