Perceivers

Perceivers are agents that interpret sensory information to form perceptual representations. In humans and other animals, perceptual systems convert physical energy from the environment—light, sound, touch, chemical stimuli—into neural signals that support recognition, judgment, and action. In artificial systems, perceivers are software or hardware components that extract features from sensors and interpret them to make decisions or drive behavior.

Perception results from the interaction of bottom-up processing with top-down influences such as expectations, prior knowledge, context, and culture. Perceivers organize sensory input into meaningful wholes using grouping, continuity, and interpretation. Individual differences in attention, expertise, motivation, and culture lead to variability in how stimuli are perceived.

Biases and limitations are common. Perceptual sets, selective attention, and contextual cues shape interpretation; phenomena such as inattentional blindness or change blindness show that perception may omit obvious information. Perceivers can improve sensitivity and flexibility through perceptual learning and adaptation, including adjusting to altered sensory inputs or using sensory substitution devices.

In research, perceivers are the subjects of experiments and the focus of studies on perception, decision making, and cognitive bias. Measures such as signal detection theory separate perceptual sensitivity from response bias. In design and human–machine interaction, understanding the capabilities and limits of perceivers helps create usable interfaces and safer systems.

Perceivers also include artificial agents, where perception modules integrate sensors, feature extractors, and classifiers to produce representations used for control, planning, or communication.