Computational Model Library

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CoDMER v. 2.0 was parameterized with ethnographic data from organizations dealing with prescribed fire and seeding native plants, to advance theory on how collective decisions emerge in ecological restoration.

Peer reviewed Garbage can model Excel reconstruction

Smarzhevskiy Ivan | Published Tuesday, August 19, 2014 | Last modified Tuesday, July 30, 2019

Reconstruction of the original code M. Cohen, J. March, and J. Olsen garbage can model, realized by means of Microsoft Office Excel 2010

Objective of our model is to simulate the emergence and operation of a technological niches (TN) in terms of actors’ interaction. A TN can be conceived as protected socio-economic space where radical innovations are developed and tested

Social trust model

Di Wang Alistair G Sutcliffe | Published Wednesday, December 17, 2014

This is a social trust model for investigating the social relationships and social networks in the real world and in social media.

Micro-level Adaptation, Macro-level Selection, and the Dynamics of Market Partitioning

César García-Díaz | Published Monday, October 19, 2015 | Last modified Monday, October 19, 2015

This model simulates the emergence of a dual market structure from firm-level interaction. Firms are profit-seeking, and demand is represented by a unimodal distribution of consumers along a set of taste positions.

This generic model simulates climate change adaptation in the form of resistance, accommodation, and retreat in coastal regions vulnerable to sea level rise and flooding. It tracks how population changes as households retreat to higher ground.

This model examines how financial and social top-down interventions interplay with the internal self-organizing dynamics of a fishing community. The aim is to transform from hierarchical fishbuyer-fisher relationship into fishing cooperatives.

TRUE GRASP

Luis García-Barrios Marco Braasch | Published Tuesday, April 03, 2018

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 Relation-Based Model (RBM) purpose is to operationalise (a form of) process-relational (PR) thinking to serve as a thinking tool for process-relational thinking among social-ecological system (SES) researchers. The development of this model itself has been a ‘Proof of concept’- exercise to see whether we actually represent process-relational thinking in a methodology that is entity-based (ABM).

The target of the agent-based model is to show the emergence, change and disappearance of fishing assemblages (focusing on processes of self-organisation) in a Mexican fishery using a process-relational view. From this view, a fishery is regarded as an assemblage in which fishing can be enabled, fishing can occur, and fish can be bought/sold. These core doings - or sub-assemblages or capacities - maintain the assemblage. Each (sub)assemblage reflects different actualisations of constellations of relations and elements (buyers, fishers, fuel, permits, vessels and wind). The RBM thereby reflects an artificial fishery in which agents (elements) and their links (relations) engage in (enabling) fishing and buying/selling.

System Narrative
How do rebel groups control territory and engage with the local economy during civil war? Charles Tilly’s seminal War and State Making as Organized Crime (1985) posits that the process of waging war and providing governance resembles that of a protection racket, in which aspiring governing groups will extort local populations in order to gain power, and civilians or businesses will pay in order to ensure their own protection. As civil war research increasingly probes the mechanisms that fuel local disputes and the origination of violence, we develop an agent-based simulation model to explore the economic relationship of rebel groups with local populations, using extortion racket interactions to explain the dynamics of rebel fighting, their impact on the economy, and the importance of their economic base of support. This analysis provides insights for understanding the causes and byproducts of rebel competition in present-day conflicts, such as the cases of South Sudan, Afghanistan, and Somalia.

Model Description
The model defines two object types: RebelGroup and Enterprise. A RebelGroup is a group that competes for power in a system of anarchy, in which there is effectively no government control. An Enterprise is a local civilian-level actor that conducts business in this environment, whose objective is to make a profit. In this system, a RebelGroup may choose to extort money from Enterprises in order to support its fighting efforts. It can extract payments from an Enterprise, which fears for its safety if it does not pay. This adds some amount of money to the RebelGroup’s resources, and they can return to extort the same Enterprise again. The RebelGroup can also choose to loot the Enterprise instead. This results in gaining all of the Enterprise wealth, but prompts the individual Enterprise to flee, or leave the model. This reduces the available pool of Enterprises available to the RebelGroup for extortion. Following these interactions the RebelGroup can choose to AllocateWealth, or pay its rebel fighters. Depending on the value of its available resources, it can add more rebels or expel some of those which it already has, changing its size. It can also choose to expand over new territory, or effectively increase its number of potential extorting Enterprises. As a response to these dynamics, an Enterprise can choose to Report expansion to another RebelGroup, which results in fighting between the two groups. This system shows how, faced with economic choices, RebelGroups and Enterprises make decisions in war that impact conflict and violence outcomes.

Displaying 10 of 824 results for "Blanca Gonzalez-Mon" clear search

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