AI engineering glossary · Reinforcement learning
What is q-learning?
Q-learning: An off-policy temporal-difference method that learns the best action values directly, updating toward the score plus the discounted maximum value over next choices. Formula: Q(s,a) = Q(s,a) + alpha*[r + gamma*max over a' of Q(s',a') - Q(s,a)]. It converges under standard conditions for small tables.
Q-learning: an example
Q(s,a)=2, r=1, best next Q=4, gamma=0.9, alpha=0.5: target 4.6, new Q = 2 + 0.5*2.6 = 3.3.
Related terms
More Reinforcement learning terms
Where you learn it
Q-learning is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.