the known input to the known output in unsupervised learning the algorithm has to find patterns in data trends in data and keep exploring the data until it reaches the output the approach followed by reinforcement learning is a trial and error method the trial and error method best explains reinforcement learning because the agent has to try out all possible actions to learn about its environment and to get maximum rewards the next parameter is feedback now in supervised learning there is a direct feedback mechanism since the machine is