Computational Model Library

Displaying 10 of 240 results for "Julio C%C3%A9sar Acosta%E2%80%93Prado" clear search

The objective of the model is to evaluate the impact of seasonal forecasts on a farmer’s net agricultural income when their crop choices have different and variable costs and returns.

CPNorm

Ruth Meyer | Published Sunday, June 04, 2017 | Last modified Tuesday, June 13, 2017

CPNorm is a model of a community of harvesters using a common pool resource where adhering to the optimal extraction level has become a social norm. The model can be used to explore the robustness of norm-driven cooperation in the commons.

Expectation-Based Bayesian Belief Revision

C Merdes Momme Von Sydow Ulrike Hahn | Published Monday, June 19, 2017 | Last modified Monday, August 06, 2018

This model implements a Bayesian belief revision model that contrasts an ideal agent in possesion of true likelihoods, an agent using a fixed estimate of trusting its source of information, and an agent updating its trust estimate.

Policy Formulation for Public Administration - Innovation

Bashar Ourabi | Published Tuesday, August 29, 2017 | Last modified Tuesday, August 29, 2017

Innovation a byproduct of the intellectual capital, requires a new paradigm for the production constituents. Human Capital HC,Structural capital SC and relational capital RC become key for intellectual capital and consequently for innovation.

This is the agent-based model of information market evolution. It simulates the influences of the transition from material to electronic carriers of information, which is modelled by the falling price of variable production factor. It demonstrates that due to zero marginal production costs, the competition increases, the market becomes unstable, and experience various phases of evolution leading to market monopolization.

In CmLab we explore the implications of the phenomenon of Conservation of Money in a modern economy. This is one of a series of models exploring the dynamics of sustainable economics – PSoup, ModEco, EiLab, OamLab, MppLab, TpLab, CmLab.

06b EiLab_Model_I_V5.00 NL

Garvin Boyle | Published Saturday, October 05, 2019

EiLab - Model I - is a capital exchange model. That is a type of economic model used to study the dynamics of modern money which, strangely, is very similar to the dynamics of energetic systems. It is a variation on the BDY models first described in the paper by Dragulescu and Yakovenko, published in 2000, entitled “Statistical Mechanics of Money”. This model demonstrates the ability of capital exchange models to produce a distribution of wealth that does not have a preponderance of poor agents and a small number of exceedingly wealthy agents.

This is a re-implementation of a model first built in the C++ application called Entropic Index Laboratory, or EiLab. The first eight models in that application were labeled A through H, and are the BDY models. The BDY models all have a single constraint - a limit on how poor agents can be. That is to say that the wealth distribution is bounded on the left. This ninth model is a variation on the BDY models that has an added constraint that limits how wealthy an agent can be? It is bounded on both the left and right.

EiLab demonstrates the inevitable role of entropy in such capital exchange models, and can be used to examine the connections between changing entropy and changes in wealth distributions at a very minute level.

This agent-based model explores the dynamics between human behavior and vaccination strategies during COVID-19 pandemics. It examines how individual risk perceptions influence behaviors and subsequently affect epidemic outcomes in a simulated metropolitan area resembling New York City from December 2020 to May 2021.

Agents modify their daily activities—deciding whether to travel to densely populated urban centers or stay in less crowded neighborhoods—based on their risk perception. This perception is influenced by factors such as risk perception threshold, risk tolerance personality, mortality rate, disease prevalence, and the average number of contacts per agent in crowded settings. Agent characteristics are carefully calibrated to reflect New York City demographics, including age distribution and variations in infection probability and mortality rates across these groups. The agents can experience six distinct health statuses: susceptible, exposed, infectious, recovered from infection, dead, and vaccinated (SEIRDV). The simulation focuses on the Iota and Alpha variants, the dominant strains in New York City during the period.

We simulate six scenarios divided into three main categories:
1. A baseline model without vaccinations where agents exhibit no risk perception and are indifferent to virus transmission and disease prevalence.

Ant Colony Optimization for infrastructure routing

Igor Nikolic Emile Chappin P W Heijnen | Published Wednesday, March 05, 2014 | Last modified Saturday, March 24, 2018

The mode implements a variant of Ant Colony Optimization to explore routing on infrastructures through a landscape with forbidden zones, connecting multiple sinks to one source.

Exploring social psychology theory for modelling farmer decision-making

James Millington | Published Tuesday, September 18, 2012 | Last modified Saturday, April 27, 2013

To investigate the potential of using Social Psychology Theory in ABMs of natural resource use and show proof of concept, we present an exemplary agent-based modelling framework that explicitly represents multiple and hierarchical agent self-concepts

Displaying 10 of 240 results for "Julio C%C3%A9sar Acosta%E2%80%93Prado" clear search

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