Reinforcement Learning: Teaching AI Through Trial and Error
Artificial intelligence (AI) has come a long way in recent years, with machines now able to perform tasks that were once thought to be the exclusive domain of humans. One of the most exciting areas of AI research is reinforcement learning, a technique that allows machines to learn through trial and error.
Reinforcement learning is a type of machine learning that involves training an AI agent to perform a task by rewarding it for making correct decisions and punishing it for making incorrect ones. The agent learns by exploring its environment and trying different actions, receiving feedback in the form of rewards or penalties based on the outcomes of those actions.