The integration of artificial intelligence (AI) into our daily lives has become increasingly prevalent in recent years. From virtual assistants to self-driving cars, AI has the potential to revolutionize the way we interact with technology. However, as AI becomes more advanced, it is important to consider how humans will interact with these machines. This is where hierarchical reinforcement learning comes into play.
Reinforcement learning is a type of machine learning where an agent learns to make decisions by interacting with its environment. The agent receives rewards or punishments based on its actions, and its goal is to maximize its reward over time.