Computational Model Library

Displaying 10 of 191 results for "David Nortes-Martinez" clear search

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.

Hybrid Climate Assessment Model (HCAM)

Peer-Olaf Siebers | Published Friday, February 15, 2019

Our Hybrid Climate Assessment Model (HCAM) aims to simulate the behaviours of individuals under the influence of climate change and external policy makings. In our proposed solution we use System Dynamics (SD) modelling to represent the physical and economic environments. Agent-Based (AB) modelling is used to represent collections of individuals that can interact with other collections of individuals and the environment. In turn, individual agents are endowed with an internal SD model to track their psychological state used for decision making. In this paper we address the feasibility of such a scalable hybrid approach as a proof-of-concept. This novel approach allows us to reuse existing rigid, but well-established Integrated Assessment Models (IAMs), and adds more flexibility by replacing aggregate stocks with a community of vibrant interacting entities.

Our illustrative example takes the settings of the U.S., a country that contributes to the majority of the global carbon footprints and that is the largest economic power in the world. The model considers the carbon emission dynamics of individual states and its relevant economic impacts on the nation over time.

Please note that the focus of the model is on a methodological advance rather than on applying it for predictive purposes! More details about the HCAM are provided in the forthcoming JASSS paper “An Innovative Approach to Multi-Method Integrated Assessment Modelling of Global Climate Change”, which is available upon request from the authors (contact peer-olaf.siebers@nottingham.ac.uk).

ForagerNet3_Demography_V3

Andrew White | Published Tuesday, November 29, 2016

The ForagerNet3_Demography model is a non-spatial ABM designed to serve as a platform for exploring several aspects of hunter-gatherer demography.

A generalized organizational agent- based model (ABM) containing both formal organizational hierarchy and informal social networks simulates organizational processes that occur over both formal network ties and informal networks.

Land-Livelihood Transitions

Nicholas Magliocca Daniel G Brown Erle C Ellis | Published Monday, September 09, 2013 | Last modified Friday, September 13, 2013

Implemented as a virtual laboratory, this model explores transitions in land-use and livelihood decisions that emerge from changing local and global conditions.

We demonstrate how a simple model of community associated Methicillin-resistant Staphylococcus aureus (CA-MRSA) can be easily constructed by leveraging the statecharts and ReLogo capabilities in Repast Simphony.

Peer reviewed Co-adoption of low-carbon household energy technologies

Mart van der Kam Maria Lagomarsino Elie Azar Ulf Hahnel David Parra | Published Tuesday, August 29, 2023 | Last modified Friday, February 23, 2024

The model simulates the diffusion of four low-carbon energy technologies among households: photovoltaic (PV) solar panels, electric vehicles (EVs), heat pumps, and home batteries. We model household decision making as the decision marking of one person, the agent. The agent decides whether to adopt these technologies. Hereby, the model can be used to study co-adoption behaviour, thereby going beyond traditional diffusion models that focus on the adop-tion of single technologies. The combination of these technologies is of particular interest be-cause (1) using the energy generated by PV solar panels for EVs and heat pumps can reduce emissions associated with transport and heating, respectively, and (2) EVs, heat pumps, and home batteries can help to integrate PV solar panels in local electricity grids by offering flexible demand (EVs and heat pumps) and energy storage (home batteries and EVs), thereby reducing grid impacts and associated upgrading costs.

The purpose of the model is to represent realistic adoption and co-adoption behaviour. This is achieved by grounding the decision model on the risks-as-feelings model (Loewenstein et al., 2001), theory from environmental and social psychology, and empirically informing agent be-haviour by survey-data among 1469 people in the Swiss region Romandie.

The model can be used to construct scenarios for the diffusion of the four low-carbon energy technologies depending on different contexts, and as a virtual experimentation environment for ex ante evaluation of policy interventions to stimulate adoption and co-adoption.

Linear Threshold

Kaushik Sarkar | Published Saturday, November 03, 2012 | Last modified Saturday, April 27, 2013

NetLogo implementation of Linear Threshold model of influence propagation.

Agent-based model of risk behavior in adolescence

N Schuhmacher P Van Geert L Ballato | Published Monday, June 24, 2013 | Last modified Monday, April 08, 2019

The computer model simulates the development of a social network (i.e. formation of friendships and cliques), the (dyadic) interactions between pupils and the development of similarities and differences in their behavioral profiles.

The Urban Traffic Simulator is an agent-based model developed in the Unity platform. The model allows the user to simulate several autonomous vehicles (AVs) and tune granular parameters such as vehicle downforce, adherence to speed limits, top speed in mph and mass. The model allows researchers to tune these parameters, run the simulator for a given period and export data from the model for analysis (an example is provided in Jupyter Notebook).

The data the model is currently able to output are the following:

Displaying 10 of 191 results for "David Nortes-Martinez" clear search

This website uses cookies and Google Analytics to help us track user engagement and improve our site. If you'd like to know more information about what data we collect and why, please see our data privacy policy. If you continue to use this site, you consent to our use of cookies.
Accept