AI GlossaryQ-LearningENTRY — Reinforcement Learning
[Reinforcement Learning]
Q-Learning.
A reinforcement learning algorithm that learns the value of actions in states to determine optimal behavior.
In-depth explanation
01Q-learning learns a Q-function that estimates the expected future reward for taking an action in a state. It's model-free (doesn't need environment model) and off-policy (can learn from any experience). Deep Q-Networks (DQN) combine Q-learning with neural networks to handle large state spaces, achieving human-level performance on Atari games.
Examples
02EX. 01
Atari game playing
EX. 02
Resource allocation
More in Reinforcement Learning
0301Policy GradientPolicy Gradient methods are a class of algorithms in reinforcement learning that optimize the policy directly by using the gradient of the expected reward with respect to the policy parameters.02Reinforcement LearningMachine learning where an agent learns to make decisions by taking actions and receiving rewards or penalties.
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