PGに簡単なゲームのやり方を学習させる Vol.1 - まずはQ学習を理解する

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PG
- Q
@shohu33

ATARI

PG
PG

(policy)

PG
PG

PG
Q
( ) ( or
) (
) Q

"Q-Learning Tutorial". Mnemosyne Studio.
http://mnemstudio.org/path-ﬁnding-q-learning-tutorial.htm

6
5

1. (Gamma)
2. Q 0
3. :
3.1
3.2 5 :
3.2.1
3.2.2
3.2.3 Q
Q(state, action) = R(state, action) + Gamma * Max[Q(next state, all...

1. (Gamma)

(Gamma) 0 1
0 ( )
0.8

[ ]

100

2. Q( ) 0

0
1 5
100
Q( )
0( )

3.1

RANDOM

3.2 5

3.2.1

3 5

3.2.2

3.2.3 Q
Q(state, action) = R(state, action) + Gamma * Max[Q(next state, all actions)]

今回、部屋1 から部屋5 に移動する⾏動を選んだので
Q
state=1, action=5, Gamma=0.8, next state=5, all actions = 1,4,5
Q

Q
Q
5
1,4,5
Q

3.2.4

3.2.6 5

3.3

3.1

3
1
Q(state, action) = R(state, action) + Gamma * Max[Q(next state, all actions)]
Q(3, 1) = R(3, 1) + 0.8 * Max[Q(1, 3), Q...

1 5
5
5 Q(state, action) = R(state, action) + Gamma * Max[Q(next state, all actions)]
Q(1, 5) = R(1, 5) + 0.8 * Max[Q(5, 1...

Q
Q
2
Q 2 → 3 → 1 → 5
OR
2 → 3 → 4 → 5
5

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