Computational Model Library

Displaying 10 of 1184 results for "Ian M Hamilton" clear search

Individual bias and organizational objectivity

Bo Xu | Published Monday, April 15, 2013 | Last modified Monday, April 08, 2019

This model introduces individual bias to the model of exploration and exploitation, simulates knowledge diffusion within organizations, aiming to investigate the effect of individual bias and other related factors on organizational objectivity.

Food trade networks represent a complex system where food is periodically produced in different regions of the world. Food is continuously stocked and traded. Food security in a globalised world is vulnerable to shocks. We present DARTS, a new agent based model that models monthly dynamics of food production, trade, stocking, consumption and food security for different interconnected world regions and a city state. Agents in different regions differ in their harvest seasons, wealth (rich and poor), degree of urbanisation and connection to domestic and global markets. DARTS was specifically designed to model direct and indirect effects of shocks in the food system. We introduce a new typology of 6 distinct shock types and analyse their impact on food security, modelling local and global effects and short term and longer term effects. An second important scientific novelty of the model is that DARTS can also model indirect effects of shocks (cascading in space and in time, lag effects due to trade and food stock buffering). A third important scientific novelty of the model is its’ capability of modelling food security at different scales, in which the rural/urban divide and differences in (intra-annually varying) production and trade connections play a key role. At the time of writing DARTS is yet insufficiently parameterised for accurate prediction for real world regions and cities. Simulations for a hypothetical in silico world with 3 regions and a city state show that DARTS can reproduce rich and complex dynamics with analogues in the real world. The scientific interest is more on deepening insight in process dynamics and chains of events that lead to ultimate shock effects on food security.

ACT: Agent-based model of Critical Transitions

Igor Nikolic Oscar Kraan Steven Dalderop Gert Jan Kramer | Published Wednesday, October 18, 2017 | Last modified Monday, August 27, 2018

ACT is an ABM based on an existing conceptualisation of the concept of critical transitions applied to the energy transition. With the model we departed from the mean-field approach simulated relevant actor behaviour in the energy transition.

Collective Cognition in Online Conversations

Paul Dwyer | Published Saturday, November 28, 2009 | Last modified Saturday, April 27, 2013

Used in working paper: MEASURING COLLECTIVE COGNITION IN ONLINE CONVERSATIONS

Universal Darwinism in Dutch Greenhouses

Julia Kasmire | Published Wednesday, May 09, 2012 | Last modified Saturday, April 27, 2013

An ABM, derived from a case study and a series of surveys with greenhouse growers in the Westland, Netherlands. Experiments using this model showshow that the greenhouse horticulture industry displays diversity, adaptive complexity and an uneven distribution, which all suggest that the industry is an evolving system.

We compare the effect of four activation regimes by measuring the appropriate opinion clustering statistics and also the number of emergent extremists.

Inquisitiveness in ad hoc teams

Davide Secchi | Published Sunday, October 18, 2015 | Last modified Thursday, June 11, 2020

This model builds on inquisitiveness as a key individual disposition to expand the bounds of their rationality. It represents a system where teams are formed around problems and inquisitive agents integrate competencies to find ‘emergent’ solutions.

Agent-based model of intergroup conflict in divided communities.

Cultural transmission in structured populations

Luke Premo | Published Wednesday, November 13, 2024

This structured population model is built to address how migration (or intergroup cultural transmission), copying error, and time-averaging affect regional variation in a single selectively neutral discrete cultural trait under different mechanisms of cultural transmission. The model allows one to quantify cultural differentiation between groups within a structured population (at equilibrium) as well as between regional assemblages of time-averaged archaeological material at two different temporal scales (1,000 and 10,000 ticks). The archaeological assemblages begin to accumulate only after a “burn-in” period of 10,000 ticks. The model includes two different representations of copying error: the infinite variants model of copying error and the finite model of copying error. The model also allows the user to set the variant ceiling value for the trait in the case of the finite model of copying error.

Displaying 10 of 1184 results for "Ian M Hamilton" clear search

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