Q-Learning

AI and Machine Learning · Reinforcement Learning · 1989 · q-learning.yaml

Learns the value of each state-action pair directly, converging to the optimal policy without ever modelling the transitions.

• supersedescorrects · extends
• classifiesspecializes · part-of
• substitutes forapproximates · alternative-to
• depends onrequires · validates

Colour is the family; a dashed line is the second member of it.

This node

• specializesis a specific case of Temporal Difference Learningthe bootstrapped target is the best next action's value

Referenced by

• correctsDeep Q-Network fixes a defect in thisa table cannot cover a high-dimensional state space
• alternative-toPolicy Gradient is a competing approach to thisoptimises the policy itself instead of a value function

References

• Background — Q-learning on Wikipedia