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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 model implements a double auction financial markets with two types of agents: rational and noise. The model aims to study the impact of different compensation structure on the market stability and market quantities as prices, volumes, spreads.
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.
The agent-based simulation is set to work on information that is either (a) functional, (b) pseudo-functional, (c) dysfunctional, or (d) irrelevant. The idea is that a judgment on whether information falls into one of the four categories is based on the agent and its network. In other words, it is the agents who interprets a particular information as being (a), (b), (c), or (d). It is a decision based on an exchange with co-workers. This makes the judgment a socially-grounded cognitive exercise. The uFUNK 1.0.2 Model is set on an organization where agent-employee work on agent-tasks.
How can a strictly egalitarian social system give way to a stratified society if all of its members punish each other for any type of selfish behavior? This model examines the role of prestige bias in constant and variable environments on the development of hierarchies of wealth.
The model examines the dynamics of herd growth in African pastoral systems. We used it to examine the role of scale (herd size) stochasticity (in mortality, fertility, and offtake) on herd growth.
This version of the accumulated copying error (ACE) model is designed to address the following research question: how does finite population size (N) affect the coefficient of variation (CV) of a continuous cultural trait under the assumptions that the only source of copying error is visual perception error and that the continuous trait can take any positive value (i.e., it has no upper bound)? The model allows one to address this question while assuming the continuous trait is transmitted via vertical transmission, unbiased transmission, prestige biased transmission, mean conformist transmission, or median conformist transmission. By varying the parameter, p, one can also investigate the effect of population size under a mix of vertical and non-vertical transmission, whereby on average (1-p)N individuals learn via vertical transmission and pN individuals learn via either unbiased transmission, prestige biased transmission, mean conformist transmission, or median conformist transmission.
ICARUS is a multi-agent compliance inspection model (ICARUS - Inspecting Compliance to mAny RUleS). The model is applicable to environments where an inspection agency, via centrally coordinated inspections, examines compliance in organizations which must comply with multiple provisions (rules). The model (ICARUS) contains 3 types of agents: entities, inspection agency and inspectors / inspections. ICARUS describes a repeated, simultaneous, non-cooperative game of pure competition. Agents have imperfect, incomplete, asymmetric information. Entities in each move (tick) choose a pure strategy (comply/violate) for each rule, depending on their own subjective assessment of the probability of the inspection. The Inspection Agency carries out the given inspection strategy.
A more detailed description of the model is available in the .nlogo file.
Full description of the model (in line with the ODD+D protocol) and the analysis of the model (including verification, validation and sensitivity analysis) can be found in the attached documentation.
Here we share the raw results of the social experiments of the paper “Gossip and competitive altruism support cooperation in a Public Good Game” by Giardini, Vilone, Sánchez, Antonioni, under review for Philosophical Transactions B. The experiment is thoroughly described there, in the following we summarize the main features of the experimental setup. The authors are available for further clarifications if requested.
Participants were recruited from the LINEEX subjects pool (University of Valencia Experimental Economics lab). 160 participants mean age = 21.7 years; 89 female) took part in this study in return for a flat payment of 5 EUR and the opportunity to earn an additional payment ranging from 8 to 16 EUR (mean total payment = 17.5 EUR). 80 subjects, divided into 5 groups of 16, took part in the competitive treatment while other 80 subjects participated in the non-competitive treatment. Laboratory experiments were conducted at LINEEX on September 16th and 17th, 2015.
This model aims at creating agent populations that have “personalities”, as described by the Big Five Model of Personality. The expression of the Big Five in the agent population has the following properties, so that they resemble real life populations as closely as possible:
-The population mean of each trait is 0.5 on a scale from 0 to 1.
-The population-wide distribution of each trait approximates a normal distribution.
-The intercorrelations of the Big Five are close to those observed in the Literature.
The literature used to fit the model was a publication by Dimitri van der Linden, Jan te Nijenhuis, and Arnold B. Bakker:
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We study three obstacles of the expansion of contract rice farming in the Mekong Delta (MKD) region. The failure of buyers in building trust-based relationship with small-holder farmers, unattractive offered prices from the contract farming scheme, and limited rice processing capacity have constrained contractors from participating in the large-scale paddy field program. We present an agent-based model to examine the viability of contract farming in the region from the contractor perspective.
The model focuses on financial incentives and trust, which affect the decision of relevant parties on whether to participate and honor a contract. The model is also designed in the context of the MKD’s rice supply chain with two contractors engaging in the contract rice farming scheme alongside an open market, in which both parties can renege on the agreement. We then evaluate the contractors’ performances with different combinations of scenarios related to the three obstacles.
Our results firstly show that a fully-equipped contractor who opportunistically exploits a relatively small proportion (less than 10%) of the contracted farmers in most instances can outperform spot market-based contractors in terms of average profit achieved for each crop. Secondly, a committed contractor who offers lower purchasing prices than the most typical rate can obtain better earnings per ton of rice as well as higher profit per crop. However, those contractors in both cases could not enlarge their contract farming scheme, since either farmers’ trust toward them decreases gradually or their offers are unable to compete with the benefits from a competitor or the spot market. Thirdly, the results are also in agreement with the existing literature that the contract farming scheme is not a cost-effective method for buyers with limited rice processing capacity, which is a common situation among the contractors in the MKD region.
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