output by finding trends and associations in the data coming to reinforcement learning the agent here is a lot like a human child just like how a baby is clueless about the world initially the agent also has no idea about its environment but as it explores the environment it starts learning it learns from the mistakes it makes and it basically learns from its experience now let's look at the approach followed when it comes to supervised learning it's quite simple like I mentioned earlier all that the algorithm has to do is map