Obesity is a result of a long-term energy imbalance due to decisions associated with energy intake and expenditure. Those decisions fit the definition of heuristics: cognitive processes with a rapid and effortless implementation which can be very effective in dealing with scenarios that threaten an organism’s viability. We study the implementation and evaluation of heuristics, and their associated actions, using agent-based simulations in environments where the distribution and degree of richness of energetic resources is varied in space and time. Artificial agents utilize foraging strategies, combining movement, active perception, and consumption, while also actively modifying their capacity to store energy—a “thrifty gene” effect—based on three different heuristics. We show that the selective advantage associated with higher energy storage capacity depends on both the agent’s foraging strategy and heuristic, as well as being sensitive to the distribution of resources, with the existence and duration of periods of food abundance and scarcity being crucial. We conclude that a ”thrifty genotype” is only beneficial in the presence of behavioral adaptations that encourage overconsumption and sedentariness, as well as seasonality and uncertainty in the food distribution.