It is well documented that cooperation may not be achieved in societies where self-interested agents are engaging in Prisoner’s Dilemma scenarios. In this paper we demonstrate, in contrast, that agent societies that use human-inspired emotions within their decision making, can reach stability in cooperation. Our work makes use of the Ortony, Clore, and Collins (OCC) model of emotions and we analyse the evolutionary stability of two different implementations that make use of key emotions from this model. Firstly, we consider an agent society that solely make use of this model of emotions for the agents’ decision making. Secondly we look at a model that extends the emotional agents with a model for representing mood. We set out a proof that shows that our emotional agents are an evolutionarily stable strategy when playing against a worst-case scenario strategy. The proof demonstrates that our established model of emotional agents enables evolutionary stability to be achieved, without modification to this model. In contrast, the model of moody agents was shown not to be an evolutionarily stable strategy. Our analysis sheds light on the nature of cooperation within agent societies and the useful role that simulated emotions can play in the agents’ decision making and the society as a whole.
Intelligent and autonomous systems

Collenette, J, Atkinson, K, Bloembergen, D, & Tuyls, K. (2020). Stability of cooperation in societies of emotional and moody agents. In Proceedings of the Artificial Life Conference 2019 (pp. 467–474). doi:10.1162/isal_a_00205