Computational Model Library

This NetLogo model illustrates the cultural evolution of pro-environmental behaviour patterns. It illustrates how collective behaviour patterns evolve from interactions between agents and agents (in a social network) as well as agents and the affordances (action opportunities provided by the environment) within a niche. More specifically, the cultural evolution of behaviour patterns is understood in this model as a product of:

  1. The landscape of affordances provided by the material environment,
  2. Individual learning and habituation,
  3. Social learning and network structure,
  4. Personal states (such as habits and attitudes), and

GRASP world

Gert Hofstede | Published Tue Apr 16 13:34:52 2019

This agent-based model investigates group longevity in a population in a foundational way, using theory on social relations and culture. It is the first application of the GRASP meta-model for social agents, containing elements of Groups, Rituals, Affiliation, Status, and Power. It can be considered an exercise in artificial sociality: a culture-general, content-free base-line trust model from which to engage in more specific studies. Depending on cultural settings for individualism and power distance, as well as settings for xenophobia and for the increase of trust over group life, the GRASP world model generates a variety of patters. Number of groups ranges from one to many, composition from random to segregated, and pattern genesis from rapid to many hundreds of time steps. This makes GRASP world an instrument that plausibly models some basic elements of social structure in different societies.

This program simulates a group of hunter-gatherer (households) moving randomly over an artificial landscapoe pulated with resources randomly distributed (a Gaussian distribution). To survive, agents hunt and gather using their own labor resources and available technology. When labor and technology is not enough to compensate the resource difficulty of access, they need to cooperate. The purpose of the model is to analyze the consequences of cooperation on cultural diversity: the more the agents cooperate, the more their culture (a 10 componenet vector) is updated to imitate the culture of cooperative agents. The less the agent cooperates, the more different its culture becomes.

The largely dominant meritocratic paradigm of highly competitive Western cultures is rooted on the belief that success is due mainly, if not exclusively, to personal qualities such as talent, intelligence, skills, smartness, efforts, willfulness, hard work or risk taking. Sometimes, we are willing to admit that a certain degree of luck could also play a role in achieving significant material success. But, as a matter of fact, it is rather common to underestimate the importance of external forces in individual successful stories. It is very well known that intelligence (or, more in general, talent and personal qualities) exhibits a Gaussian distribution among the population, whereas the distribution of wealth - often considered a proxy of success - follows typically a power law (Pareto law), with a large majority of poor people and a very small number of billionaires. Such a discrepancy between a Normal distribution of inputs, with a typical scale (the average talent or intelligence), and the scale invariant distribution of outputs, suggests that some hidden ingredient is at work behind the scenes. In a recent paper, with the help of this very simple agent-based model realized with NetLogo, we suggest that such an ingredient is just randomness. In particular, we show that, if it is true that some degree of talent is necessary to be successful in life, almost never the most talented people reach the highest peaks of success, being overtaken by mediocre but sensibly luckier individuals. As to our knowledge, this counterintuitive result - although implicitly suggested between the lines in a vast literature - is quantified here for the first time. It sheds new light on the effectiveness of assessing merit on the basis of the reached level of success and underlines the risks of distributing excessive honors or resources to people who, at the end of the day, could have been simply luckier than others. With the help of this model, several policy hypotheses are also addressed and compared to show the most efficient strategies for public funding of research in order to improve meritocracy, diversity and innovation.

EthnoCultural Tag model (ECT)

David Hales Bruce Edmonds | Published Fri Oct 16 13:26:37 2015 | Last modified Wed May 9 10:04:58 2018

Captures interplay between fixed ethnic markers and culturally evolved tags in the evolution of cooperation and ethnocentrism. Agents evolve cultural tags, behavioural game strategies and in-group definitions. Ethnic markers are fixed.

This spatially explicit agent-based model addresses how effective foraging radius (r_e) affects the effective size–and thus the equilibrium cultural diversity–of a structured population composed of central-place foraging groups.

DITCH --- A Model of Inter-Ethnic Partnership Formation

Ruth Meyer Laurence Lessard-Phillips Huw Vasey | Published Wed Nov 5 18:07:16 2014 | Last modified Tue Feb 2 18:00:00 2016

The DITCH model has been developed to investigate partner selection processes, focusing on individual preferences, opportunities for contact, and group size to uncover how these may lead to differential rates of inter-­ethnic marriage.

Shared Norms and the Evolution of Ethnic Markers

Nathan Rollins | Published Fri Jan 22 17:35:22 2010 | Last modified Sat Apr 27 20:18:45 2013

The publication and mathematical model upon which this ABM is based shows one mechanism that can lead to stable behavioral and cultural traits between groups.

TechNet_04: Cultural Transmission in a Spatially-Situated Network

Andrew White | Published Mon Oct 8 19:36:07 2012 | Last modified Sat Apr 27 20:18:48 2013

The TechNet_04 is an abstract model that embeds a simple cultural tranmission process in an environment where interaction is structured by spatially-situated networks.

THE STATUS ARENA

Gert Hofstede Jillian Student Mark R Kramer | Published Wed Jun 8 13:27:12 2016 | Last modified Tue Jan 9 19:35:05 2018

Status-power dynamics on a playground, resulting in a status landscape with a gender status gap. Causal: individual (beauty, kindness, power), binary (rough-and-tumble; has-been-nice) or prior popularity (status). Cultural: acceptability of fighting.

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