Computational Model Library

Cultural Evolution of Sustainable Behaviours: Landscape of Affordances Model (1.2.0)

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
  5. Cultural niche construction, or the modulation of affordances within a niche.

More particularly, the model illustrates how changes in the landscape of affordances can trigger nonlinear changes in collective behaviour patterns. Even linear changes in affordances can trigger nonlinear uptakes of collective behaviour patterns. The model also shows how several behavioural cultures can emerge from the same environment and even within the same network.

The model is an elaboration of Kurt Lewin’s heuristic equation, B = f(P, E), where behaviour (B) is a function (f) of the person (P) and the environment (E). The model introduces several feedback loops (1–5 above) to Lewin’s equation, and thus provides an entry-point into studying the evolution of dynamical and complex behavioural systems over time. The model should be considered an abstract model, since many of its parameters are unspecifiable due to limits to current understanding of human (social) behaviour. However, the model can be tuned to replicate real-world macro patterns, and can be used as a sandbox environment to locate tipping points in social systems.

Figure2.png

Release Notes

See ODD protocol (comes with download).

Associated Publications

doi: https://doi.org/10.31234/osf.io/w6dpa

Cite as:

APA
Kaaronen, R. O., & Strelkovskii, N. (2019, October 9). Cultural Evolution of Sustainable Behaviours: Pro-Environmental Tipping Points in an Agent-Based Model. https://doi.org/10.31234/osf.io/w6dpa
MLA
Kaaronen, Roope O., and Nikita Strelkovskii. “Cultural Evolution of Sustainable Behaviours: Pro-environmental Tipping Points in an Agent-based Model.” PsyArXiv, 9 Oct. 2019. Web.
Chicago
Kaaronen, Roope O., and Nikita Strelkovskii. 2019. “Cultural Evolution of Sustainable Behaviours: Pro-environmental Tipping Points in an Agent-based Model.” PsyArXiv. October 9. doi:10.31234/osf.io/w6dpa.

Cultural Evolution of Sustainable Behaviours: Landscape of Affordances Model 1.2.0

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
  5. Cultural niche construction, or the modulation of affordances within a niche.

More particularly, the model illustrates how changes in the landscape of affordances can trigger nonlinear changes in collective behaviour patterns. Even linear changes in affordances can trigger nonlinear uptakes of collective behaviour patterns. The model also shows how several behavioural cultures can emerge from the same environment and even within the same network.

The model is an elaboration of Kurt Lewin’s heuristic equation, B = f(P, E), where behaviour (B) is a function (f) of the person (P) and the environment (E). The model introduces several feedback loops (1–5 above) to Lewin’s equation, and thus provides an entry-point into studying the evolution of dynamical and complex behavioural systems over time. The model should be considered an abstract model, since many of its parameters are unspecifiable due to limits to current understanding of human (social) behaviour. However, the model can be tuned to replicate real-world macro patterns, and can be used as a sandbox environment to locate tipping points in social systems.

Release Notes

See ODD protocol (comes with download).

Version Submitter First published Last modified Status
1.2.0 Roope Oskari Kaaronen Wed Dec 4 14:47:01 2019 Mon Jan 20 05:51:45 2020 Published Peer Reviewed https://doi.org/10.25937/z8x6-2v73

Discussion

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