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.
All users of models published in the library must cite model authors when they use and benefit from their code.
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.
Displaying 10 of 67 results for 'E Frances Cassirer'
The model aims to simulate predator-prey relationships in an agricultural setting. The focus lies on avian communities and their effect on different pest organisms (here: pest birds, rodents, and arthropod pests). Since most case studies focused on the impact on arthropod pests (AP) alone, this model attempts to include effects on yield outcome. By incorporating three treatments with different factor levels (insectivorous bird species, falconry, nest box density) an experimental setup is given that allows for further statistical analysis to identify an optimal combination of the treatments.
In light of a global decline of birds, insects, and many other groups of organisms, alternative practices of pest management are heavily needed to reduce the input of pesticides. Avian pest control therefore poses an opportunity to bridge the disconnect between humans and nature by realizing ecosystem services and emphasizing sustainable social ecological systems.
The HUMan impact on LANDscapes (HUMLAND) model has been developed to track and quantify the intensity of different impacts on landscapes at the continental level. This agent-based model focuses on determining the most influential factors in the transformation of interglacial vegetation with a specific emphasis on burning organized by hunter-gatherers. HUMLAND integrates various spatial datasets as input and target for the agent-based model results. Additionally, the simulation incorporates recently obtained continental-scale estimations of fire return intervals and the speed of vegetation regrowth. The obtained results include maps of possible scenarios of modified landscapes in the past and quantification of the impact of each agent, including climate, humans, megafauna, and natural fires.
The Communication-Based Model of Perceived Descriptive Norm Dynamics in Digital Networks (COMM-PDND) is an agent-based model specifically created to examine the dynamics of perceived descriptive norms in the context of digital network structures. The model, developed as part of a master’s thesis titled “The Dynamics of Perceived Descriptive Norms in Digital Network Publics: An Agent-Based Simulation,” emphasizes the critical role of communication processes in norm formation. It focuses on the role of communicative interactions in shaping perceived descriptive norms.
The COMM-PDND is tuned to explore the effects of normative deviance in digital social networks. It provides functionalities for manipulating agents according to their network position, and has a versatile set of customizable parameters, making it adaptable to a wide range of research contexts.
This purpose of this model is to understand how the coupled demographic dynamics of herds and households constrain the growth of livestock populations in pastoral systems.
This is an extension of the original RAGE model (Dressler et al. 2018), where we add learning capabilities to agents, specifically learning-by-doing and social learning (two processes central to adaptive (co-)management).
The extension module is applied to smallholder farmers’ decision-making - here, a pasture (patch) is the private property of the household (agent) placed on it and there is no movement of the households. Households observe the state of the pasture and their neighrbours to make decisions on how many livestock to place on their pasture every year. Three new behavioural types are created (which cannot be combined with the original ones): E-RO (baseline behaviour), E-LBD (learning-by-doing) and E-RO-SL1 (social learning). Similarly to the original model, these three types can be compared regarding long-term social-ecological performance. In addition, a global strategy switching option (corresponding to double-loop learning) allows users to study how behavioural strategies diffuse in a heterogeneous population of learning and non-learning agents.
An important modification of the original model is that extension agents are heterogeneous in how they deal with uncertainty. This is represented by an agent property, called the r-parameter (household-risk-att in the code). The r-parameter is catch-all for various factors that form an agent’s disposition to act in a certain way, such as: uncertainty in the sensing (partial observability of the resource system), noise in the information received, or an inherent characteristic of the agent, for instance, their risk attitude.
This is a replication of the SequiaBasalto model, originally built in Cormas by Dieguez Cameroni et al. (2012, 2014, Bommel et al. 2014 and Morales et al. 2015). The model aimed to test various adaptations of livestock producers to the drought phenomenon provoked by climate change. For that purpose, it simulates the behavior of one livestock farm in the Basaltic Region of Uruguay. The model incorporates the price of livestock, fodder and paddocks, as well as the growth of grass as a function of climate and seasons (environmental submodel), the life cycle of animals feeding on the pasture (livestock submodel), and the different strategies used by farmers to manage their livestock (management submodel). The purpose of the model is to analyze to what degree the common management practices used by farmers (i.e., proactive and reactive) to cope with seasonal and interannual climate variations allow to maintain a sustainable livestock production without depleting the natural resources (i.e., pasture). Here, we replicate the environmental and livestock submodel using NetLogo.
One year is 368 days. Seasons change every 92 days. Each day begins with the growth of grass as a function of climate and season. This is followed by updating the live weight of cows according to the grass height of their patch, and grass consumption, which is determined based on the updated live weight. After consumption, cows grow and reproduce, and a new grass height is calculated. Cows then move to the patch with less cows and with the highest grass height. This updated grass height value will be the initial grass height for the next day.
Riparian forests are one of the most vulnerable ecosystems to the development of biological invasions, therefore limiting their spread is one of the main challenges for conservation. The main factors that explain plant invasions in these ecosystems are the capacity for both short- and long-distance seed dispersion, and the occurrence of suitable habitats that facilitate the establishment of the invasive species. Large floods constitute an abiotic filter for invasion.
This model simulates the spatio-temporal spread of the woody invader Gleditsia. triacanthos in the riparian forest of the National Park Esteros de Farrapos e Islas del Río Uruguay, a riparian system in the coast of the Uruguay river (South America). In this model, we represent different environmental conditions for the development of G. triacanthos, long- and short-distance spread of its fruits, and large floods as the main factor of mortality for fruit and early stages.
Field results show that the distribution pattern of this invasive species is limited by establishment, i.e. it spreads locally through the expansion of small areas, and remotely through new invasion foci. This model recreates this dispersion pattern. We use this model to derive management implications to control the spread of G. triacanthos
The SIM-VOLATILE model is a technology adoption model at the population level. The technology, in this model, is called Volatile Fatty Acid Platform (VFAP) and it is in the frame of the circular economy. The technology is considered an emerging technology and it is in the optimization phase. Through the adoption of VFAP, waste-treatment plants will be able to convert organic waste into high-end products rather than focusing on the production of biogas. Moreover, there are three adoption/investment scenarios as the technology enables the production of polyhydroxyalkanoates (PHA), single-cell oils (SCO), and polyunsaturated fatty acids (PUFA). However, due to differences in the processing related to the products, waste-treatment plants need to choose one adoption scenario.
In this simulation, there are several parameters and variables. Agents are heterogeneous waste-treatment plants that face the problem of circular economy technology adoption. Since the technology is emerging, the adoption decision is associated with high risks. In this regard, first, agents evaluate the economic feasibility of the emerging technology for each product (investment scenarios). Second, they will check on the trend of adoption in their social environment (i.e. local pressure for each scenario). Third, they combine these two economic and social assessments with an environmental assessment which is their environmental decision-value (i.e. their status on green technology). This combination gives the agent an overall adaptability fitness value (detailed for each scenario). If this value is above a certain threshold, agents may decide to adopt the emerging technology, which is ultimately depending on their predominant adoption probabilities and market gaps.
The model aims to illustrate how Earned Value Management (EVM) provides an approach to measure a project’s performance by comparing its actual progress against the planned one, allowing it to evaluate trends to formulate forecasts. The instance performs a project execution and calculates the EVM performance indexes according to a Performance Measurement Baseline (PMB), which integrates the description of the work to do (scope), the deadlines for its execution (schedule), and the calculation of its costs and the resources required for its implementation (cost).
Specifically, we are addressing the following questions: How does the risk of execution delay or advance impact cost and schedule performance? How do the players’ number or individual work capacity impact cost and schedule estimations to finish? Regardless of why workers cause delays or produce overruns in their assignments, does EVM assess delivery performance and help make objective decisions?
To consider our model realistic enough for its purpose, we use the following patterns: The model addresses classic problems of Project Management (PM). It plays the typical task board where workers are assigned to complete a task backlog in project performance. Workers could delay or advance in the task execution, and we calculate the performance using the PMI-recommended Earned Value.
This model has been created with and for the researcher-farmers of the Muonde Trust (http://www.muonde.org/), a registered Zimbabwean non-governmental organization dedicated to fostering indigenous innovation. Model behaviors and parameters (mashandiro nemisiyano nedzimwe model) derive from a combination of literature review and the collected datasets from Muonde’s long-term (over 30 years) community-based research. The goals of this model are three-fold (muzvikamu zvitatu):
A) To represent three components of a Zimbabwean agro-pastoral system (crops, woodland grazing area, and livestock) along with their key interactions and feedbacks and some of the human management decisions that may affect these components and their interactions.
B) To assess how climate variation (implemented in several different ways) and human management may affect the sustainability of the system as measured by the continued provisioning of crops, livestock, and woodland grazing area.
C) To provide a discussion tool for the community and local leaders to explore different management strategies for the agro-pastoral system (hwaro/nzira yekudyidzana kwavanhu, zvipfuo nezvirimwa), particularly in the face of climate change.
Displaying 10 of 67 results for 'E Frances Cassirer'