Q-learning is a model-free reinforcement learning algorithm to learn the value of an action in a particular state. It does not require a model of the ...

May 7, 2023 · Popular model-free techniques include Q-learning and deep Q-networks (DQN). 3. Policy Gradient Methods. The primary goal of policy gradient ...

Nov 23, 2023 · Q-learning is a model-free reinforcement learning algorithm to learn the value of an action in a particular state. It does not require a model ...

Q learning is reinforcement learning that iteratively adjusts state-action policy by maintaining a table of state-action pairs, while deep Q learning ...

May 15, 2024 · Q-learning is a fascinating and widely used reinforcement learning type with applications ranging from robotics to video game AI.

Feb 18, 2019 · This article pursues to highlight in a non-exhaustive manner the main type of algorithms used for reinforcement learning (RL).

There are several algorithms that can be used to train reinforcement learning agents, such as Q-learning, policy gradient methods, and actor-critic methods.

Q-learning is a type of reinforcement learning. With reinforcement learning, a machine learning model is trained to mimic the way animals or children learn.