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.
New theoretical agent-based model of population-wide adoption of prosocial common-pool behavior with four parameters (initial percent of adopters, pressure to change behavior, synergy from behavior, and population density); dynamics in behavior, movement, freeriding, and group composition and size; and emergence of multilevel group selection. Theoretical analysis of model’s dynamics identified six regions in model’s parameter space, in which pressure-synergy combinations lead to different outcomes: extinction, persistence, and full adoption. Simulation results verified the theoretical analysis and demonstrated that increases in density reduce number of pressure-synergy combinations leading to population-wide adoption; initial percent of contributors affects underlying behavior and final outcomes, but not size of regions or transition zones between them; and random movement assists adoption of prosocial common-pool behavior.
In 1985 Dr Michael Palmiter, a high school teacher, first built a very innovative agent-based model called “Simulated Evolution” which he used for teaching the dynamics of evolution. In his model, students can see the visual effects of evolution as it proceeds right in front of their eyes. Using his schema, small linear changes in the agent’s genotype have an exponential effect on the agent’s phenotype. Natural selection therefore happens quickly and effectively. I have used his approach to managing the evolution of competing agents in a variety of models that I have used to study the fundamental dynamics of sustainable economic systems. For example, here is a brief list of some of my models that use “Palmiter Genes”:
- ModEco - Palmiter genes are used to encode negotiation strategies for setting prices;
- PSoup - Palmiter genes are used to control both motion and metabolic evolution;
- TpLab - Palmiter genes are used to study the evolution of belief systems;
- EffLab - Palmiter genes are used to study Jevon’s Paradox, EROI and other things.
Organisms, Individuals and Organizations face the dilemma of exploration vs. exploitation
Identifying the optimal trade-off between the two is a challenge
Too much exploration (e.g. gaining new knowledge) can be detrimental to day-to-day survival and too much exploitation (applying existing knowledge) could be detrimental to long term survival esp. if conditions change over time
The purpose of the model is to investigate how the amount of resources acquired (wealth/success) is related to persistence with the strategy of local exploration under different resource distributions, availability of resources over time and cost of relocation
The model is a combination of a spatially explicit, stochastic, agent-based model for wild boars (Sus scrofa L.) and an epidemiological model for the Classical Swine Fever (CSF) virus infecting the wild boars.
The original model (Kramer-Schadt et al. 2009) was used to assess intrinsic (system immanent host-pathogen interaction and host life-history) and extrinsic (spatial extent and density) factors contributing to the long-term persistence of the disease and has further been used to assess the effects of intrinsic dynamics (Lange et al. 2012a) and indirect transmission (Lange et al. 2016) on the disease course. In an applied context, the model was used to test the efficiency of spatiotemporal vaccination regimes (Lange et al. 2012b) as well as the risk of disease spread in the country of Denmark (Alban et al. 2005).
References: See ODD model description.
We develop a spatial, evolutionary model of the endogenous formation and dissolution of groups using a renewable common pool resource. We use this foundation to measure the evolutionary pressures at different organizational levels.
TRUE GRASP (Tree Recruitment Under Exotic GRAsses in a Savanna-Pineland)
is a socio-ecological agent-based model (ABM) and role playing game (RPG) for farmers and other stakeholders involved in rural landscape planning.
The purpose of this model is to allow actors to explore the individual and combined effects - as well as tradeoffs - of three methods of controlling exotic grasses in pine savannas: fire, weeding, and grazing cattle.
Design of TRUE GRASP is based on 3 years of socio-ecological fieldwork in a human-induced pine savanna in La Sepultura Biosphere Reserve (SBR) in the Mexican state of Chiapas. In this savanna, farmers harvest resin from Pinus oocarpa, which is used to produce turpentine and other products. However, long term persistence of this activity is jeopardized by low tree recruitment due to exotic tall grass cover in the forest understory (see Braasch et al., 2017). The TRUE GRASP model provides the user with different management strategies for controlling exotic grass cover and avoiding possible regime shifts, which in the case of the SBR would jeopardize resin harvesting.
The model represents an archetypical fishery in a co-evolutionary social-ecological environment, capturing different dimensions of trust between fishers and fish buyers for the establishment and persistence of self-governance arrangements.
We seek to improve understanding of roles enzyme play in soil food webs. We created an agent-based simulation of a simple food web that includes enzymatic activity. The model was used in a publication, Moore et al. (in press; Biochemistry).
Our societal belief systems are pruned by evolution, informing our unsustainable economies. This is one of a series of models exploring the dynamics of sustainable economics – PSoup, ModEco, EiLab, OamLab, MppLab, TpLab, CmLab.
The model employs an agent-based model for exploring the victim-centered approach to identifying human trafficking and the approach’s effectiveness in an abstract representation of migrant flows.