Zero-Shot Learning is an AI approach that enables models to learn to recognise new classes or concepts without explicit training examples. This is achieved by leveraging existing knowledge and transferring it to unseen classes. Zero-Shot Learning is useful when acquiring labelled data for all possible classes is challenging or unfeasible.
Constraint Satisfaction Problems are mathematical problems where a set of variables must satisfy a given set of constraints. CSPs are used in AI for…