What does Q-learning mean?

Q-learning is a term for an algorithm structure representing model-free reinforcement learning. By evaluating policy and using stochastic modeling, Q-learning finds the best path forward in a Markov decision process.


Techopedia explains Q-learning

The technical makeup of the Q-learning algorithm involves an agent, a set of states and a set of actions per state.

The Q function uses weights for various steps in conjunction with a discount factor in order to value rewards.

Although it may seem like a simple idea, Q-learning is of paramount importance in many types of reinforcement learning and deep learning models. One of the best examples is where deep Q-learning is used to help machine learning programs to learn game-play strategies in various types of video games, for example, in Atari games from the 1980s. Here a convolutional neural network takes samples of game-play in order to work up a stochastic model that will help the computer know how to play the game better over time.

Q-learning has abundant potential for helping to advance artificial intelligence and machine learning.


Share this Term

  • Facebook
  • LinkedIn
  • Twitter

Survey: Why Is There Still a Gender Gap in Tech?

Do you work in the tech industry? Help us learn more about why the gender gap still exists in tech by taking this quick survey! Survey respondents will also be entered to win a $100 Amazon Gift Card!

Related Reading


Technology TrendsMachine LearningData Science

Trending Articles

Newest Articles

Go back to top