Waseda.L#1/@tkf

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@tkf
Waseda.L

2009 7 11

@tkf ( Waseda.L ) 2009 7 11 1 / 23

:
( )
@tkf, id:tkf41,
:

M1

:
/ /

@tkf ( Waseda.L ) 2009 7 11 2 / 23

— —

(Recurrent Neural Network)

→

@tkf ( Waseda.L ) 2009 7 11 3 / 23

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:

:
?
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?
@tkf ( Waseda.L ) 2009 7 11 4 / 23

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( )
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“ ”↔“ ” ?
:

@tkf ( Waseda.L ) 2009 7 11 5 / 23

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@tkf ( Waseda.L ) 2009 7 11 6 / 23

— ?—

@tkf ( Waseda.L ) 2009 7 11 7 / 23

— —

:

PC
(NN ) (CPU, )
??? (*.exe)
(*.c, *.py)

@tkf ( Waseda.L ) 2009 7 11 8 / 23

— RNN —
Output neurons

Input neurons

Context neurons
(Internal states)

Neural Network(NN)
= NN
Recurrent Neural Network(RNN)

@tkf ( Waseda.L ) 2009 7 11 9 / 23

— RNN —

Output

Input

Output

Input
Contex neuron
Output

Input

@tkf ( Waseda.L ) 2009 7 11 10 / 23

Output

Input

Output

Input

Output

Input

@tkf ( Waseda.L ) 2009 7 11 11 / 23

R K

U L

@tkf ( Waseda.L ) 2009 7 11 12 / 23

RK RL R
R K

UK UL U
c 2

U L c 1 K L

(Sugita and Tani, 2008)
@tkf ( Waseda.L ) 2009 7 11 12 / 23

RK ??
Own behaviors
UK UL
c 3 Other’s behaviors
c 2

RK RL R
c 1

UK UL
U
K L

→
→1
1
→
@tkf ( Waseda.L ) 2009 7 11 13 / 23

NN
?
:
, ,

, ,

,

@tkf ( Waseda.L ) 2009 7 11 14 / 23

— —

RK ??
Own behaviors
UK UL
c 3 Other’s behaviors
c 2

RK RL R
c 1

UK UL
U
K L

RL
RL
RL
@tkf ( Waseda.L ) 2009 7 11 15 / 23

— —

@tkf ( Waseda.L ) 2009 7 11 16 / 23

— - —

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

0.0 UL UL UL UL UL UL UL UL UK UK UK 0.0 UL UL UL UL UL UL UL UL UL UK UK
0.1 UL UL UL UL UL UL UL UL UL UK UK 0.1 UL UL UL UL UL UL UL UL UL UK UK
0.5 0.5

→
UL UL UL UL UL UL UL UL UK UK UK UL UL UL UL UL UL UL UL UL UK UK
0.6 UL UL UL UL UL UL UL UK UK XK RK 0.6 UL UL XK XK XK XK XK XK XK XK RK
0.7 UL UL UL UL UL XK XK XK XK RK RK 0.7 RL RL RL RL RL RK RK RK RK RK RK
0.8 UL UL XK XK XK RK RK RK RK RK RK 0.8 RL RL RL RL RL RL RK RK RK RK RK
0.9 XK XK RK RK RK RK RK RK RK RK RK 0.9 RL RL RL RL RL RL RK RK RK RK RK
1.0 RK RK RK RK RK RK RK RK RK RK RK 1.0 RL RL RL RL RL RL RL RK RK RK RK

RL RL

RK RL R

UK UL U
c 2

c 1 K L

@tkf ( Waseda.L ) 2009 7 11 17 / 23

(1)

(2)
(3)
( )

:

@tkf ( Waseda.L ) 2009 7 11 18 / 23

@tkf ( Waseda.L ) 2009 7 11 19 / 23

Appendix — ?—

?

@tkf ( Waseda.L ) 2009 7 11 20 / 23

Appendix — (SOM+RNN) —

( )
x(t)−µi 2
exp − σ
si (t) = ( ) , i∈S (1)
∑ x(t)−µ j 2
j∈S exp − σ

ci (t) = a(ui (t)) = sigmoid(ui (t)), i ∈ C (2)
{
ci (t), i ∈ S
zi (t) = , i∈N (3)
si (t), i ∈ C
∑
j
ui (t + 1) = (1 − i )ui (t) + i w z j (t), i ∈ N
i
j∈N
(4)
exp (ui (t + 1))
gi (t + 1) = ∑ ( ), i ∈ S (5)
j∈S exp u j (t + 1)
∑
y(t + 1) = gi (t + 1)µi (6)
i∈S

@tkf ( Waseda.L ) 2009 7 11 21 / 23

Appendix — (3D) —

UK
UL
RK 1
RL 0.8
0.6
0.4
0.2
PC 3 0
-0.2
-0.4
-0.6
-0.8
-1

1

0.5

0

PC 2 -0.5

-1

-1.5
2 2.5
1 1.5
-2 0 0.5
-1 -0.5
PC 1

@tkf ( Waseda.L ) 2009 7 11 22 / 23

Appendix — —
?

“ ” “
”
:
1
1

0.5
0.5

0
0

PC 2
PC 2

-0.5
-0.5

-1
-1
+20mm
UK -1.5 +10mm
-1.5 0mm
UL -10mm
RK -20mm
RL -2
-2 -1 -0.5 0 0.5 1 1.5 2 2.5
-1 -0.5 0 0.5 1 1.5 2 2.5
PC 1
PC 1

RL
@tkf ( Waseda.L ) 2009 7 11 23 / 23

Waseda.L#1/@tkf

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