Citation: Learning without feedback: Neuroscientist helps uncover the influence of unsupervised learning on humans and machines (2024, October 18) retrieved 21 July 2025 from https://medicalxpress ...

Reinforcement learning is a type of machine learning where an agent learns by interacting with its environment and receiving feedback in the form of rewards or penalties.

reinforcement learning is quite different than supervised/unsupervised learning. reinforcement learning requires an environment (perhaps simulated) in which the agent can act so that it can get ...

the gain of an attribute \(A\) is a good way to choose how to split examples in decision tree learning: the higher the gain, the better the question. there is much more to decision tree learning, ...