Computational Model Library

Displaying 10 of 1165 results for "Ian M Hamilton" clear search

Smallholder Behavioural Decisions During Times of Drought Stress

Samantha Dobbie | Published Sunday, September 15, 2013 | Last modified Saturday, September 27, 2014

An empirical ABM of smallholder decisions in times of drought stress.

Simulating the evolution of the human family

Paul Smaldino | Published Wednesday, November 29, 2017

The (cultural) evolution of cooperative breeding in harsh environments.

Social Innovation Model

Jiin Jung | Published Monday, April 28, 2025

This research aims to uncover the micro-mechanisms that drive the macro-level relationship between cultural tolerance and innovation. We focus on the indirect influence of minorities—specifically, workers with diverse domain expertise—within collaboration networks. We propose that minority influence from individuals with different expertise can serve as a key driver of organizational innovation, particularly in dynamic market environments, and that cultural tolerance is critical for enabling such minority-induced innovation. Our model demonstrates that seemingly conflicting empirical patterns between cultural tightness/looseness and innovation can emerge from the same underlying micro-mechanisms, depending on parameter values. A systematic simulation experiment revealed an optimal cultural configuration: a medium level of tolerance (t = 0.6) combined with low consistency (κ = 0.05) produced the fastest adaptation to abrupt market changes. These findings provide evidence that indirect minority influence is a core micro-mechanism linking cultural tolerance to innovation.

Mast seeding model

Giangiacomo Bravo Lucia Tamburino | Published Saturday, September 08, 2012 | Last modified Saturday, April 27, 2013

Purpose of the model is to perform a “virtual experiment” to test the predator satiation hypothesis, advanced in literature to explain the mast seeding phenomenon.

ALABAMA-ABM

Bartosz Bartkowski Michael Strauch | Published Wednesday, March 04, 2020

A simple model that aims to demonstrate the influence of agri-environmental payments on land-use patterns in a virtual landscape. The landscape consists of grassland (which can be managed extensively or intensively) and a river. Agri-environmental payments are provided for extensive management of grassland. Additionally, there are boni for (a) extensive grassland in proximity of the river; and (b) clusters (“agglomerations”) of extensive grassland. The farmers, who own randomly distributed grassland patches, make decisions either on the basis of simple income maximization or they maximize only up to an income threshold beyond which they seize making changes in management. The resulting landscape pattern is evaluated by means of three simple models for (a) agricultural yield, (b) habitat/biodiversity and (c) water quality. The latter two correspond to the two boni. The model has been developed within a small project called Aligning Agent-Based Modelling with Multi-Objective Land-Use Allocation (ALABAMA).

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.

Societal Simulator v203

Tim Gooding | Published Tuesday, October 01, 2013 | Last modified Friday, November 28, 2014

Designed to capture the evolutionary forces of global society.

Peer reviewed Horse population dynamics

Nika Galic | Published Tuesday, November 12, 2013 | Last modified Wednesday, October 29, 2014

This model investigates the link between prescribed growth in body size, population dynamics and density dependence through population feedback on available resources.

This Repast Simphony model simulates genomic admixture during the farming expansion of human groups from mainland Asia into the Papuan dominated islands of Southeast Asia during the Neolithic period.

NK model for multilevel adaptation

Dario Blanco Fernandez | Published Wednesday, November 30, 2022

Previous research on organizations often focuses on either the individual, team, or organizational level. There is a lack of multidimensional research on emergent phenomena and interactions between the mechanisms at different levels. This paper takes a multifaceted perspective on individual learning and autonomous group formation and turnover. To analyze interactions between the two levels, we introduce an agent-based model that captures an organization with a population of heterogeneous agents who learn and are limited in their rationality. To solve a task, agents form a group that can be adapted from time to time. We explore organizations that promote learning and group turnover either simultaneously or sequentially and analyze the interactions between the activities and the effects on performance. We observe underproportional interactions when tasks are interdependent and show that pushing learning and group turnover too far might backfire and decrease performance significantly.

Displaying 10 of 1165 results for "Ian M Hamilton" clear search

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