Computational Emotions Encourage Collective Behavior in Population Dynamics

We evaluate how a computational model of emotions may enable collective behav-ior in a predator-prey system. Our cellular automata model combines emotion-based decision rules with simple communication. Although there are a number of human psychological theories of emotion, it is generally agreed that emotions increase our ability to interact with our environment. Human emotions may have initially evolved for survival, showing many commonalities with predator-prey scenarios. Additionally, groups of prey will exchange information about their surroundings to increase their sur-vival. We therefore define emotions for predators and prey based on these theories of emotions and Ekman’s basic emotions. Our system describes the interactions of foxes that feed on rabbits that feed on carrots. Emotions are used by foxes and rabbits and encode data pertaining to survival. We examine variations of the communication, and to what extent an individual’s decisions should be based on the communicated emotion versus the personal emotion. We find that the emotion rules and communication allow each population to cooperate and improve their population’s fitness. 196