Agent-Based Simulation of Stakeholder Behaviour through Evolutionary Game Theory
Aquaculture organizations establish facilities at the coast in Frøya, Norway. The facilities block the surrounding area from fishing and cause environmental damage to close natural resources. Fishers who depend on those natural resources get the opportunity to influence the aquaculture expansion through complaints about the municipality’s coastal plan. Statistics show that fishers don’t complain as much as expected. This work aims to investigate why. An agent-based simulation is developed in order to model the fishers as intelligent agents with complex interaction. Fishermen’s decision making is simulated through an artificial neural network which adapts its behavior (i.e. weights) by “learning-by-imitation”, a method in evolutionary game theory, from other stakeholders’ behavior in the environment. The promising results show that with further development the simulation system may be part of a decision support system that promotes policies that are fair for the stakeholders.
Keywordscomputational intelligence agent-based model simulation learning by imitation evolutionary game theory artificial neural network strategical decision making
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- 1.Davidsson, P.: Agent based social simulation: A computer science view. Journal of Artificial Societies and Social Simulation 5(1) (January 2002)Google Scholar
- 2.Smith, M.: Evolution and the Theory of Games. Cambridge University Press (1982)Google Scholar
- 4.Tiller, R., Richards, R., Salgado, H., Strand, H., Moe, E., Ellis, J.: Assessing stakeholder adaptive capacity to salmon aquaculture in Norway. Consilience: The Journal of Sustainable Development 11(1), 62–96 (2014)Google Scholar
- 7.Rebaudo, F., Crespo-Perez, V., Silvain, J.-F., Dangles, O.: Agent-based modeling of human-induced spread of invasive species in agricultural landscapes: Insights from the potato moth in Ecuador. Journal of Artificial Societies and Social Simulation 14(3), 7 (2011)Google Scholar