Appetitive motivation is a process inherent to human beings, which stimulates behaviors directed at searching, pursuing, and achieving specific objectives based on a set of impulses. Consequently, the motivational process has been considered part of the control system in some cognitive architectures because it can influence the execution of goal-directed behaviors of different kinds. Different motivational computational systems integrate physiological needs and environmental conditions to produce human-like behavior in artificial agents. However, these motivational computational systems limit abstract properties defining a motivational state; consequently, the adaptability characterizing motivated human behavior does not arise. In this research line, this article proposes a bioinspired model for generating the motivational state from the physiological condition, capable of triggering processes involved in developing appetitive behavior. The proposed system incorporates bloodstream and viscerosensory biomarkers to represent a motivational state of hunger regulated by energy homeostasis or balance control. The proposed model is based on neuroscientific studies and implemented under a distributed paradigm emulating the way it happens in living beings. The validation of the proposed model’s functioning uses study cases comparing the proposal’s results with neuroscientific evidence.