Our mission is to help computational modelers at all levels engage in the establishment and adoption of community standards and good practices for developing and sharing computational models. Model authors can freely publish their model source code in the Computational Model Library alongside narrative documentation, open science metadata, and other emerging open science norms that facilitate software citation, reproducibility, interoperability, and reuse. Model authors can also request peer review of their computational models to receive a DOI.
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We also maintain a curated database of over 7500 publications of agent-based and individual based models with additional detailed metadata on availability of code and bibliometric information on the landscape of ABM/IBM publications that we welcome you to explore.
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The purpose of this hybrid ABM is to answer the question: where is the best place for a new swimming pool in a region of Krakow (in Poland)?
The model is well described in ODD protocol, that can be found in the end of my article published in JASSS journal (available online: http://jasss.soc.surrey.ac.uk/22/1/1.html ). Comparison of this kind of models with spatial interaction ones, is presented in the article. Before developing the model for different purposes, area of interest or services, I recommend reading ODD protocol and the article.
I published two films on YouTube that present the model: https://www.youtube.com/watch?v=iFWG2Xv20Ss , https://www.youtube.com/watch?v=tDTtcscyTdI&t=1s
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Swidden Farming is designed to explore the dynamics of agricultural land management strategies.
An algorithm implemented in NetLogo that can be used for searching resources.
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?
Under the Kyoto Protocol, governments agreed on and accepted CO2 reduction targets in order to counter climate change. In Europe one of the main policy instruments to meet the agreed reduction targets is CO2 emission-trading (CET), which was implemented as of January 2005. In this system, companies active in specific sectors must be in the possession of CO2 emission rights to an amount equal to their CO2 emission. In Europe, electricity generation accounts for one-third of CO2 emissions. Since the power generation sector, has been liberalized, reregulated and privatized in the last decade, around Europe autonomous companies determine the sectors’ CO2 emission. Short-term they adjust their operation, long-term they decide on (dis)investment in power generation facilities and technology selection. An agent-based model is presented to elucidate the effect of CET on the decisions of power companies in an oligopolistic market. Simulations over an extensive scenario-space show that there CET does have an impact. A long-term portfolio shift towards less-CO2 intensive power generation is observed. However, the effect of CET is relatively small and materializes late. The absolute emissions from power generation rise under most scenarios. This corresponds to the dominant character of current capacity expansion planned in the Netherlands (50%) and in Germany (68%), where companies have announced many new coal based power plants. Coal is the most CO2 intensive option available and it seems surprising that even after the introduction of CET these capacity expansion plans indicate a preference for coal. Apparently in power generation the economic effect of CO2 emission-trading is not sufficient to outweigh the economic incentives to choose for coal.
In order to test how prosocial strategies (compassionate altruism vs. reciprocity) grow over time, we developed an evolutionary simulation model where artificial agents are equipped with different emotionally-based drivers that vary in strength. Evolutionary algorithms mimic the evolutionary selection process by letting the chances of agents conceiving offspring depend on their fitness. Equipping the agents with heritable prosocial strategies allows for a selection of those strategies that result in the highest fitness. Since some prosocial attributes may be more successful than others, an initially heterogeneous population can specialize towards altruism or reciprocity. The success of particular prosocial strategies is also expected to depend on the cultural norms and environmental conditions the agents live in.
This is an agent-based model, simulating wolf (Canis Lupus) reappearance in the Netherlands. The model’s purpose is to allow researchers to investigate the reappearance of wolves in the Netherlands and the possible effect of human interference. Wolf behaviour is modelled according to the literature. The suitability of the Dutch landscape for wolf settlement has been determined by Lelieveld (2012) [1] and is transformed into a colour-coded map of the Netherlands. The colour-coding is the main determinant of wolf settlement. Human involvement is modelled through the public opinion, which varies according to the size, composition and behaviour of the wolf population.
[1] Lelieveld, G.: Room for wolf comeback in the Netherlands, (2012).
This model was developed to test the usability of evolutionary computing and reinforcement learning by extending a well known agent-based model. Sugarscape (Epstein & Axtell, 1996) has been used to demonstrate migration, trade, wealth inequality, disease processes, sex, culture, and conflict. It is on conflict that this model is focused to demonstrate how machine learning methodologies could be applied.
The code is based on the Sugarscape 2 Constant Growback model, availble in the NetLogo models library. New code was added into the existing model while removing code that was not needed and modifying existing code to support the changes. Support for the original movement rule was retained while evolutionary computing, Q-Learning, and SARSA Learning were added.
Objective is to simulate policy interventions in an integrated demand-supply model. The underlying demand function links both sides. Diffusion proceeds if interactions distribute awareness (Epidemic effect) and rivalry reduces the market price (Probit effect). Endogeneity is given due to the fact that consumer awareness as well as their willingness-to-pay drives supply-side rivalry. Firm´s entry and exit decisions as well as quantity and price settings are driven by Cournot competition.
The Carington model is designed to provide insights into the factors affecting informal health care for older adults. It encompasses older adults, caregivers, and factors affecting informal health care. The Carington model includes no submodels.
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