Q-learning

A model-free reinforcement technique in machine learning and data mining that compares available actions to states of the expected actions for a given machine state.

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A model-free reinforcement technique in machine learning and data mining that compares available actions to states of the expected actions for a given machine state. Q-learning is able to find the optimal set of states for any given finite Markov decision process (MDP).

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Further Resources

Title

Author

Link

Type

Date

A Deep Q-Learning Agent for the L-Game with Variable Batch Training

Petros Giannakopoulos, Yannis Cotronis

http://arxiv.org/abs/1802.06225v1

Academic paper

A Simple Reinforcement Learning Mechanism for Resource Allocation in LTE-A Networks with Markov Decision Process and Q-Learning

Einar Cesar Santos

http://arxiv.org/abs/1709.09312v1

Academic paper

Balancing Two-Player Stochastic Games with Soft Q-Learning

Jordi Grau-Moya, Felix Leibfried, Haitham Bou-Ammar

http://arxiv.org/abs/1802.03216v1

Academic paper

Bayesian Q-learning with Assumed Density Filtering

Heejin Jeong, Daniel D. Lee

http://arxiv.org/abs/1712.03333v1

Academic paper

Combining policy gradient and Q-learning

Brendan O'Donoghue, Remi Munos, Koray Kavukcuoglu, Volodymyr Mnih

http://arxiv.org/abs/1611.01626v3

Academic paper

References

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