Connetionism

Connectionism is a way of understanding how the brain and artificial intelligence work by modeling them as networks of interconnected units, similar to neurons. In this approach, knowledge is stored in the strength of connections between these units. When information is processed, signals travel through these connections, activating certain pathways. Connectionist models can learn and adapt by adjusting the connection strengths based on experience, allowing for pattern recognition and problem-solving. This approach helps explain how complex cognitive functions emerge from simple, coordinated interactions between many units.