Parallel Distributed Processing

Parallel Distributed Processing (PDP) is a way of understanding how the brain and artificial systems learn and process information. Instead of relying on a single pathway, many units (like neurons) work together simultaneously, sharing and spreading out information across the network. This interconnected activity allows for efficient, flexible, and resilient processing, similar to how the brain recognizes patterns or solves problems by distributing tasks across multiple areas. PDP models are used in fields like artificial intelligence to mimic human learning and cognition, emphasizing that knowledge is stored and processed through patterns of connections rather than isolated points.