Reinforcement learning

Reinforcement Learning (RL) is the science of decision making.It is about taking suitable action to maximize reward in a particular situation.It is employed by various software and machines to find the best possible behavior or path it should take in a specific situation.Reinforcement learning differs from supervi sed learning in a way that in supervised learning the training data has the answer key with it so the model is trained with the correct answer itself whereas in reinforcement learning, there is no answer but the reinforcement agent decides what to do to perform the given task.In the absence of a training dataset, it is bound to learn from its experience.Reinforcement learning is an autonomous, self-teaching system that essentially learns by trial and error.It performs actions with the aim of maximizing rewards, or in other words, it is learning by doing in order to achieve the best outcomes.