Instance-Based Learning is an AI approach where models make predictions based on similarity to previously seen examples. Instead of generalising from a predefined set of rules, Instance-Based Learning examines specific instances and their characteristics. This approach is effective in tasks such as pattern recognition and recommendation systems.
Neuroevolution is a type of AI learning that combines neural networks and evolutionary algorithms. Neuroevolution algorithms evolve neural networks over generations, adapting them to…