Competitive Learning

Competitive learning is a process used in artificial intelligence and machine learning where models improve by competing against each other to recognize patterns. Imagine a group of students trying to learn a new topic; each student focuses on different aspects and competes to understand it best. Similarly, in competitive learning, different parts of a model "compete" to become the most accurate at classifying or recognizing data. The best-performing model or neuron gets to adjust and improve, while others learn from its success, leading to a system that becomes increasingly effective at identifying patterns and making decisions over time.