Generative Adversarial Imitation Learning

Generative Adversarial Imitation Learning (GAIL) is a method used in artificial intelligence to teach machines how to perform tasks by observing human behavior. It works like a competition: one part of the AI tries to mimic the human actions (the generator), while another part evaluates how well it is doing (the discriminator). The goal is for the generator to produce actions that are indistinguishable from those of the human. This approach allows AI to learn complex tasks without needing explicit instructions, relying instead on examples of skilled performance to guide its learning process.