CoMSES Net maintains cyberinfrastructure to foster FAIR data principles for access to and (re)use of computational models. Model authors can publish their model code in the Computational Model Library with documentation, metadata, and data dependencies and support these FAIR data principles as well as best practices for software citation. Model authors can also request that their model code be peer reviewed to receive a DOI. All users of models published in the library must cite model authors when they use and benefit from their code.
CoMSES Net also maintains a curated database of over 7500 publications of agent-based and individual based models with additional metadata on availability of code and bibliometric information on the landscape of ABM/IBM publications that we welcome you to explore.
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)  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.
 Lelieveld, G.: Room for wolf comeback in the Netherlands, (2012).
“Food for all” (FFD) is an agent-based model designed to study the evolution of cooperation for food storage. Households face the social dilemma of whether to store food in a corporate stock or to keep it in a private stock.
To our knowledge, this is the first agent-based simulation of continuous-time PGGs (where participants can change contributions at any time) which are much harder to realise within both laboratory and simulation environments.
Work related to this simulation has been published in the following journal article:
Vu, Tuong Manh, Wagner, Christian and Siebers, Peer-Olaf (2019) ‘ABOOMS: Overcoming the Hurdles of Continuous-Time Public Goods Games with a Simulation-Based Approach’ Journal of Artificial Societies and Social Simulation 22 (2) 7 http://jasss.soc.surrey.ac.uk/22/2/7.html. doi: 10.18564/jasss.3995
RHEA aims to provide a methodological platform to simulate the aggregated impact of households’ residential location choice and dynamic risk perceptions in response to flooding on urban land markets. It integrates adaptive behaviour into the spatial landscape using behavioural theories and empirical data sources. The platform can be used to assess: how changes in households’ preferences or risk perceptions capitalize in property values, how price dynamics in the housing market affect spatial demographics in hazard-prone urban areas, how structural non-marginal shifts in land markets emerge from the bottom up, and how economic land use systems react to climate change. RHEA allows direct modelling of interactions of many heterogeneous agents in a land market over a heterogeneous spatial landscape. As other ABMs of markets it helps to understand how aggregated patterns and economic indices result from many individual interactions of economic agents.
The model could be used by scientists to explore the impact of climate change and increased flood risk on urban resilience, and the effect of various behavioural assumptions on the choices that people make in response to flood risk. It can be used by policy-makers to explore the aggregated impact of climate adaptation policies aimed at minimizing flood damages and the social costs of flood risk.
Our Hybrid Climate Assessment Model (HCAM) aims to simulate the behaviours of individuals under the influence of climate change and external policy makings. In our proposed solution we use System Dynamics (SD) modelling to represent the physical and economic environments. Agent-Based (AB) modelling is used to represent collections of individuals that can interact with other collections of individuals and the environment. In turn, individual agents are endowed with an internal SD model to track their psychological state used for decision making. In this paper we address the feasibility of such a scalable hybrid approach as a proof-of-concept. This novel approach allows us to reuse existing rigid, but well-established Integrated Assessment Models (IAMs), and adds more flexibility by replacing aggregate stocks with a community of vibrant interacting entities.
Our illustrative example takes the settings of the U.S., a country that contributes to the majority of the global carbon footprints and that is the largest economic power in the world. The model considers the carbon emission dynamics of individual states and its relevant economic impacts on the nation over time.
Please note that the focus of the model is on a methodological advance rather than on applying it for predictive purposes! More details about the HCAM are provided in the forthcoming JASSS paper “An Innovative Approach to Multi-Method Integrated Assessment Modelling of Global Climate Change”, which is available upon request from the authors (contact [email protected]).
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.
We compare three model estimates for the time and treatment requirements to eliminate HCV among HIV-positive MSM in Victoria, Australia: a compartmental model; an ABM parametrized by surveillance data; and an ABM with a more heterogeneous population.
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.
The CONSERVAT model evaluates the effect of social influence among farmers in the Lake Naivasha basin (Kenya) on the spatiotemporal diffusion pattern of soil conservation effort levels and the resulting reduction in lake sedimentation.