Tugevdusõppe
Tugevdusõppe, also known as reinforcement learning, is a machine learning paradigm concerned with how software agents ought to take actions in an environment in order to maximize some notion of cumulative reward. It is one of the three basic machine learning paradigms, alongside supervised learning and unsupervised learning.
In reinforcement learning, the agent learns by interacting with its environment. It receives feedback in the
Key components of a reinforcement learning system include the agent, the environment, the state, the action,
Reinforcement learning has been applied to a wide range of problems, including robotics, game playing, autonomous