freeCodeCamp/curriculum/challenges/english/11-machine-learning-with-python/tensorflow/reinforcement-learning-with-q-learning-example.md

---
id: 5e8f2f13c4cdbe86b5c72da5
title: 'Reinforcement Learning With Q-Learning: Example'
challengeType: 11
videoId: RBBSNta234s
bilibiliIds:
  aid: 848073871
  bvid: BV1uL4y187Eq
  cid: 409139471
dashedName: reinforcement-learning-with-q-learning-example
---

# --question--

## --text--

Fill in the blanks to complete the following Q-Learning equation:

```py
Q[__A__, __B__] = Q[__A__, __B__] + LEARNING_RATE * (reward + GAMMA * np.max(Q[__C__, :]) - Q[__A__, __B__])
```

## --answers--

A: `state`

B: `action`

C: `next_state`

---

A: `state`

B: `action`

C: `prev_state`

---

A: `state`

B: `reaction`

C: `next_state`

## --video-solution--

1