Computational Model Library

Displaying 10 of 185 results for "Mark R Kramer" clear search

Knowledge Space Model for Opinion Dynamics

Shane Mueller | Published Thursday, September 28, 2017 | Last modified Thursday, September 20, 2018

Knowledge Space model of Opinion Dynamics.

This model is a part of an ongoing research project on Multiagent Reinforcement Learning (MARL). The ODD protocol is included in the model. In this version of the model, Proximal Policy Optimization (PPO) is designed in the agent behaviors. It also includes a designed experiment in its Behavior Space which is used in the Response Surface Methodology and training of an Artificial Neural Network (ANN) based Recommender System.

IMine is a flexible framework which can be adopt multiple criteria for convergence to solve Influence Minig problems. It can use any diffusion model, as well as resilience to compute the influence of a set of nodes base on the use case.
The code is written and tested on ‘R’ v3.5

FRAMe (Flood Resilience Agent-Based Model)

Wenhan Feng | Published Wednesday, October 22, 2025

The FRAMe (Flood Resilience Agent-Based Model) serves as a framework designed to simulate flood resilience dynamics at the community level, focusing on a rural settlement in the Mekong River Basin. Integrating empirical data from extensive surveys, Bayesian networks, and hydrological simulations, the framework quantifies resilience as a trade-off between robustness (resistance to damage) and adaptability (capacity for dynamic response). Agents include households, governments, and other actors, linked by social and governance networks that facilitate knowledge transfer, resource distribution, and risk communication. FRAMe incorporates mechanisms for flood forecasting, policy interventions (education, aid, insurance), and individual and collective decision-making, grounded in Protection Motivation Theory and MoHuB frameworks. The framework’s spatially explicit design leverages GIS data, which supports scenario testing of governance structures and stakeholder interactions. By examining policy scenarios and agent behavior, FRAMe aims to inform adaptive flood management strategies and enhance community resilience.

A spatial prisoner’s dilemma model with mobile agents, de-coupled birth-death events, and harsh environments.

Peer reviewed Ants Digging Networks

Elske van der Vaart | Published Friday, September 14, 2018

This is a NetLogo version of Buhl et al.’s (2005) model of self-organised digging activity in ant colonies. It was built for a master’s course on self-organisation and its intended use is still educational. The ants’ behavior can easily be changed by toggling switches on the interface, or, for more advanced students, there is R code included allowing the model to be run and analysed through RNetLogo.

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.

A dynamic model of social network formation on single-layer and multiplex networks with structural incentives that vary over time.

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

The Cardial Spread Model

Sean Bergin | Published Friday, September 29, 2017 | Last modified Monday, February 04, 2019

The purpose of this model is to provide a platform to test and compare four conceptual models have been proposed to explain the spread of the Impresso-Cardial Neolithic in the west Mediterranean.

Displaying 10 of 185 results for "Mark R Kramer" 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