The Energetic Dimension of Emotions: An Evolution-Based Computer Simulation with General Implications

Abstract

Viewed from an evolutionary standpoint, emotions can be understood as situation-specific patterns of energy consumption related to behaviors that have been selected by evolution for their survival value, such as environmental exploration, flight or fight, and socialization. In the present article, the energy linked with emotions is investigated by a strictly energy-based simulation of the evolution of simple autonomous agents provided with random cognitive and motor capacities and operating among food and predators. Emotions are translated into evolving patterns of energy consumption related to situation-specific behaviors. As a result, a variety of behaviors resembling emotions (“fear” of predators, attraction to food, competition and/or collaboration with other agents, and so on) emerge, each with a specific pattern of energy consumption. There is little difference between emotion-like behaviors on individual and collective levels. The fact that these patterns evolve under a strictly energetic selection regime indicates the interesting role and adaptive advantage of emotions as situation-specific energy savers. Although gained through an approach characterized by a highly reduced complexity, these findings support a quantitative understanding of emotions that may improve the existing qualitative approaches and could have far-reaching implications for further research on and conceptualization of emotions and their interactions with cognition.