According to this article:

Reinforcement learning on the other hand, which is a subset of Unsupervised learning ...

How true is this statement? Is there any scholarly discussion/writing on the classifications of Reinforcement learning?

  • $\begingroup$ The Wikipedia article clearly mentions Reinforcement learning is one of three basic machine learning paradigms, alongside supervised learning and unsupervised learning. $\endgroup$ Apr 9, 2021 at 6:52

2 Answers 2


Reinforcement learning differs from Unsupervised learning as it uses additional information regarding the expected behavior of the agent in the form of a reward function. However, it also differs from Supervised learning as it does not require any labelled data for training or testing.

So, it is neither of them. You may also refer to the wiki page of Reinforcement learning for further related details.


No, Reinforcement Learning and Unsupervised Learning are considered two different paradigms.

We can refer to the seminal book Pattern Recognition and Machine Learning by Christopher Bishop for their respective definitions:

  • Unsupervised learning:

    In other pattern recognition problems, the training data consists of a set of input vectors x without any corresponding target values. The goal in such unsupervised learning problems may be to discover groups of similar examples within the data, where it is called clustering, or to determine the distribution of data within the input space, known as density estimation, or to project the data from a high-dimensional space down to two or three dimensions for the purpose of visualization

  • Reinforcement learning:

    Finally, the technique of reinforcement learning [...] is concerned with the problem of finding suitable actions to take in a given situation in order to maximize a reward.

As you can see, their goals are completely different: while in unsupervised learning we don't have labels and we are aiming at discovering the structure of the data, in reinforcement learning we want to learn a strategy to maximize the obtained rewards according to a reward signal.


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