Q-learning

Summary

• Q-learning is a reinforcement learning technique that works by learning an action-value function that gives the expected utility of taking a given action in a given state and following a fixed policy thereafter. A strength with Q-learning is that it is able to compare the expected utility of the available actions without requiring a model of the environment.

Similar Topics

• E-learning
• M-learning
• Learning
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• Lifelong learning
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Related Topics

• Expected utility
• Reinforcement learning

  * This page is licensed under the GNU Free Documentation License. It uses material from the Wikipedia article "Q-learning".