Generative Adversarial Networks are a type of Machine Learning model that consists of two neural networks: a generator and a discriminator. GANs are used to generate synthetic data that resembles real data by learning from training examples. They find applications in image generation, video synthesis, and data augmentation.
Constraint Satisfaction Problems are mathematical problems where a set of variables must satisfy a given set of constraints. CSPs are used in AI for…