Interval timing, the ability to perceive and estimate durations in the seconds-to-minutes range, represents one of the most fundamental cognitive processes underlying adaptive behavior across species. This capacity enables organisms to extract temporal regularities from their environment, optimize foraging strategies, coordinate communication, and make predictions about future events. The paper describes a model of an active agent with an internal structure. The structure is represented by an ensemble capable of generating rhythmic activity within specific intervals. The ensemble is a network of three nodes: a half-center oscillator consisting of two nodes exciting each other in antiphase, and a trigger node with memory. The half-center oscillator excites the trigger, which, when activated, transmits activity to the agent. The frequency of trigger activation depends on its threshold value. A population timing model composed of such agents is proposed, demonstrating properties characteristic of biological systems: adherence to Weber’s Law, shift in duration estimates toward mean values, forgetting in the absence of a stimulus, and a return to homeostatic parameters. Biologically inspired timing research not only advances our understanding of time perception, evaluation, and prediction but also drives innovations in adaptive AI, robotics, and human-machine interfaces.