This walkthrough illustrates how a system following Pattern Existence Theory (PET) learns to recognize a face through repeated exposure.

The example starts with basic visual patterns—lines, curves, and spatial arrangements—detected by the visual sensor. These raw sensory patterns are passed into the short-term memory graph and are gradually associated with stable nodes like “Eye,” “Nose,” “Mouth,” and finally a composite “Face” node.

As the system encounters the same face repeatedly, an Understanding Node is formed, linking the visual pattern cluster to the concept of an individual (e.g., “Mother” or “Father”). Over time, the system reinforces this pattern with emotional associations (like comfort or attention), strengthening both recognition and attachment.

This walkthrough demonstrates:

• How multiple low-level patterns are linked into mid-level composite nodes.
• How time and recurrence strengthen recognition through reinforcement.
• How emotion and context nodes influence perception and understanding.