McCulloch-Pitts neuron model

The McCulloch-Pitts neuron model is a foundational concept in artificial intelligence, representing how neurons in the brain can process information. It depicts a simplified nerve cell that receives inputs, processes them, and produces a single output. Each input is assigned a weight, and if the combined inputs exceed a certain threshold, the neuron "fires" and produces an output (like a yes/no decision). This model illustrates the basic principles of neural networks, which are crucial for understanding more complex computational systems and artificial intelligence. Despite its simplicity, it paved the way for advancements in machine learning and cognitive science.