Home

The Cultural Simulator is an agent-based system that simulates how cultures emerge. Individuals are represented by agents that live on a grid. The interface shows the agents in colors according to their cultural vector, a list of cultural features with assigned cultural traits, e.g. the cultural feature music could have the cultural trait jazz assigned to it.

When two agents (1) have exactly the same cultural features on the cultural vector and (2) are adjacent neighbors on the grid, then they belong to the same culture. Over time, agents influence each other, transmitting their cultural traits to other neighboring agents in a Neumann radius.

As agents constantly transmit information to each other, do they all end up sharing the same culture? This really depends on the rules that are set up regarding how information is being shared, and the initial starting conditions. For example, homophily, the principle that like attracks like has proven to promote cultural diversity. The size of the grid, the size of the cultural vector, the number of traits, and the size of the Neumann neigborhood have proven to be important paramaters that affect the final levels of diversity.

The Cultural Simulator gives the option to modify many of these parameters, plus it provides the possibility to use different rule sets (which represent the models as proposed by different authors: Axelrod (1997), Flache & Macy (2011), Ulloa, Kacperski & Sancho (2016)).

The Cultural Simulator allows for elements such as random changes in the cultural vectors (mutation), errors in the selection of similar agents (selection error), simultaneous influence by several agents (multilateral social influence), and a second layer of information that serves as central repositories for group of agents (institutions). Institutions are able to influence agents indirectly - by preventing social influence (institutional influence) -, or directly through top-down and bottom-up processes (propaganda and democracy).

Finally, the Cultural Simulator includes mechanisms to explore the resilience of convergence states. These are called Events. Events introduce (1) changes to the initial parameters of the simulation, or (2) changes to the content and structure of agents and institutions throughout the simulation run. For example, a decimation event allows destruction of a chosen percentage of the agent population. A conversion event allows the introduction of foreigners traits to the institutions.

Continue with the Quick Start and start trying your parameters!