Reinforcement learning
Reinforcement learning is a type of machine learning that learns by interacting with its environment and receiving positive reinforcement for correct predictions and negative reinforcement for incorrect predictions. This type of machine learning may be used to develop autonomous vehicles. Common algorithms are temporal difference, deep adversarial networks, and Q-learning