Description: Perceptual learning is a type of learning that focuses on how experiences influence an individual’s perception. This process involves the adaptation and modification of perceptual responses through accumulated experience, allowing systems, whether human or artificial, to recognize patterns and make inferences based on sensory data. In the context of artificial intelligence, perceptual learning translates into the ability of machines to simulate human cognitive processes, such as visual and auditory perception, through architectures that mimic the functioning of the brain. This approach seeks not only to replicate the capacity for learning but also the flexibility and efficiency that characterize biological systems. Through algorithms that allow for continuous adaptation, perceptual learning becomes an essential tool for the development of intelligent systems that can interact with their environment more naturally and effectively. In summary, perceptual learning is fundamental to the evolution of artificial intelligence, as it enables machines to learn from their experiences and improve their performance in complex tasks.
