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Vo
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1
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Feb
r
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y
201
7
,
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4
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8708
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ad
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m
et
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o
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s
[
1
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,
[
2
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.
Desp
ite
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f
ec
tiv
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s
s
o
f
t
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in
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w
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d
if
f
er
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f
r
o
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lear
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n
d
ee
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o
f
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c
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co
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[
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f
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m
ass
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tan
ce
,
ac
co
r
d
in
g
to
in
d
i
v
id
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al
s
k
ill
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[
4
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th
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attr
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tes
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-
p
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ased
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t
if
ic
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i
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telli
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ce
alg
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ith
m
s
[
5
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,
th
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g
a
m
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to
r
y
tel
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eq
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to
t
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th
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b
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av
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f
th
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p
la
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[
6
]
;
an
d
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f
lo
w
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ev
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d
ac
tio
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eq
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r
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in
clu
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in
th
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g
a
m
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[
7
]
.
T
h
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p
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ce
s
s
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f
th
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s
t
u
d
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co
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s
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
J
E
C
E
Vo
l.
7
,
No
.
1
,
Feb
r
u
ar
y
201
7
:
4
5
1
–
459
452
T
ab
le
1
.
Kn
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led
g
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Ga
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Sk
ill
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lead
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ea
s
y
a
n
d
f
u
n
w
a
y
,
th
e
p
r
o
p
o
s
ed
s
er
io
u
s
g
a
m
e
is
eq
u
ip
p
ed
w
it
h
a
s
y
s
te
m
o
f
ad
ap
tatio
n
b
ased
o
n
th
e
lear
n
er
s
’
p
er
f
o
r
m
a
n
ce
s
,
i
n
o
r
d
er
,
t
o
ad
ap
t
th
e
g
a
m
e
ac
co
r
d
in
g
t
o
th
e
lev
el
o
f
t
h
e
s
tu
d
e
n
t.
A
d
is
cu
s
s
io
n
o
f
t
h
e
o
b
tain
ed
r
esu
lt
w
i
th
t
h
e
f
u
t
u
r
e
r
esear
ch
w
o
r
k
i
n
th
e
f
ield
w
ill
co
n
clu
d
e
th
is
p
ap
er
.
2.
RE
L
AT
E
D
WO
RK
A
cc
o
r
d
in
g
to
an
e
x
p
er
i
m
e
n
t
c
o
n
d
u
cted
in
t
h
e
p
ap
er
:
P
lay
e
r
P
er
f
o
r
m
an
ce
,
Satis
f
ac
tio
n
,
a
n
d
Vid
eo
Ga
m
e
E
n
j
o
y
m
en
t
[
8
]
,
it
s
h
o
w
s
h
o
w
th
e
d
i
f
f
icu
lt
y
ca
n
a
f
f
ec
t
th
e
s
ati
s
f
ac
tio
n
o
f
t
h
e
p
la
y
er
,
as
a
r
esu
lt,
to
o
ea
s
y
g
a
m
e
s
lead
s
to
b
o
r
e
d
o
m
an
d
to
o
h
ar
d
g
am
e
s
m
a
y
lead
to
f
r
u
s
tr
atio
n
.
B
ased
o
n
th
ese
r
esu
lt
s
w
e
tak
e
i
n
to
co
n
s
id
er
atio
n
t
h
e
p
la
y
er
p
r
o
f
ile,
p
lay
er
s
t
h
at
m
i
g
h
t
h
a
v
e
d
if
f
er
en
t
le
v
els
o
f
k
n
o
w
led
g
e
an
d
g
a
m
in
g
s
k
ill
s
.
Ho
w
e
v
er
,
in
t
h
is
s
tu
d
y
,
w
e
f
o
c
u
s
ed
o
n
5
attr
ib
u
tes,
r
es
u
lti
n
g
th
e
ad
ap
tatio
n
o
f
t
h
r
ee
g
a
m
e
s
k
ill
s
.
2
.
1
.
P
la
y
er
Sa
t
is
f
a
ct
io
n
A
cc
o
r
d
in
g
to
an
e
x
p
er
i
m
e
n
t
c
o
n
d
u
cted
in
t
h
e
p
ap
er
:
P
lay
e
r
P
er
f
o
r
m
an
ce
,
Satis
f
ac
tio
n
,
a
n
d
Vid
eo
Ga
m
e
E
n
j
o
y
m
en
t
[
8
]
,
it
s
h
o
w
s
h
o
w
th
e
d
i
f
f
icu
lt
y
ca
n
a
f
f
ec
t
th
e
s
ati
s
f
ac
tio
n
o
f
t
h
e
p
la
y
er
,
as
a
r
esu
lt,
to
o
ea
s
y
g
a
m
e
s
lead
s
to
b
o
r
ed
o
m
an
d
to
o
h
ar
d
g
am
e
s
m
a
y
lead
to
f
r
u
s
tr
atio
n
.
B
ased
o
n
th
ese
r
esu
lt
s
w
e
tak
e
i
n
to
co
n
s
id
er
atio
n
t
h
e
p
la
y
er
p
r
o
f
ile,
p
lay
er
s
t
h
at
m
i
g
h
t
h
a
v
e
d
if
f
er
en
t
le
v
els
o
f
k
n
o
w
led
g
e
an
d
g
a
m
in
g
s
k
ill
s
.
Ho
w
e
v
er
,
in
t
h
is
s
tu
d
y
,
w
e
f
o
c
u
s
ed
o
n
5
attr
ib
u
tes,
r
es
u
lti
n
g
th
e
ad
ap
tatio
n
o
f
t
h
r
ee
g
a
m
e
s
k
ill
s
.
2
.
2
.
Art
if
icia
l
I
nte
llig
ence
A
cc
o
r
d
in
g
to
th
e
s
t
u
d
y
R
ap
i
d
A
d
ap
tatio
n
o
f
Vid
eo
Ga
m
e
[
9
]
,
A
I
Dif
f
ic
u
lt
y
s
ca
li
n
g
i
s
o
n
e
o
f
t
h
e
m
ai
n
ele
m
e
n
ts
t
h
at
s
h
o
u
ld
b
e
ad
ap
tab
le
u
s
in
g
A
I
,
b
u
t
tal
k
i
n
g
ab
o
u
t
t
h
e
d
i
f
f
ic
u
lt
y
is
q
u
ite
lar
g
e
as
a
co
n
ce
p
t,
an
d
ag
ai
n
th
e
b
ac
k
g
r
o
u
n
d
/p
r
o
f
ile
o
f
t
h
e
p
la
y
er
is
t
h
e
m
ain
r
ep
air
to
k
n
o
w
i
f
t
h
e
g
a
m
e
is
e
as
y
/d
i
f
f
icu
lt.
I
n
th
is
p
ap
er
,
w
e
f
o
cu
s
ed
o
n
th
e
p
lay
er
,
in
o
r
d
er
t
o
g
et
h
is
in
telle
ctu
al
lev
el
to
ad
ap
t
th
e
g
a
m
e
ac
co
r
d
in
g
l
y
a
n
d
in
ad
d
itio
n
,
th
e
g
a
m
e
s
h
o
u
ld
b
e
ab
le
to
lear
n
an
d
co
llect
in
f
o
r
m
atio
n
f
r
o
m
p
la
y
er
s
t
h
e
m
o
r
e
g
a
m
es a
r
e
p
la
y
ed
.
3.
SE
R
I
O
US
G
AM
E
ADAP
T
A
T
I
O
N
T
h
e
m
ai
n
o
b
j
ec
tiv
e
o
f
th
is
cu
r
r
en
t
p
ap
er
is
to
a
d
ap
t
a
s
er
io
u
s
g
a
m
e
b
ased
o
n
s
ev
er
al
p
ar
am
eter
s
r
elate
d
to
th
e
lear
n
er
b
eh
a
v
i
o
r
s
d
u
r
in
g
t
h
e
g
a
m
e
a
n
d
t
h
e
ad
ap
tatio
n
w
ill
b
e
d
o
n
e
b
y
u
s
in
g
a
v
ar
iet
y
o
f
m
ac
h
in
e
lear
n
in
g
alg
o
r
it
h
m
s
,
e.
g
.
“
n
e
u
r
al
n
et
w
o
r
k
,
d
ec
is
io
n
t
r
ee
”,
th
e
d
escr
ip
tio
n
o
f
th
e
p
r
o
p
o
s
ed
s
er
io
u
s
g
a
m
e
a
n
d
th
e
e
s
tab
lis
h
m
en
t o
f
th
e
h
all
s
y
s
te
m
w
ill b
e
d
escr
i
b
ed
in
th
is
s
ec
tio
n
.
3
.
1
.
T
he
P
ro
ps
ed
Serio
us
G
a
m
e
“
E
Q
UAF
UN”
T
h
e
f
o
llo
w
i
n
g
g
a
m
e
“
Fi
g
u
r
e
.
1
”
p
r
esen
ts
th
e
ad
ap
tatio
n
ap
p
r
o
ac
h
,
th
e
g
a
m
e
is
b
ased
o
n
f
iv
e
o
f
t
h
e
b
asic
attr
ib
u
tes
(
A
g
e,
Se
x
,
Av
er
ag
e
o
f
r
esp
o
n
s
e
ti
m
e,
N
u
m
b
er
o
f
w
r
o
n
g
a
n
s
w
er
s
,
N
u
m
b
er
o
f
r
ed
u
n
d
an
t
f
au
lts
)
i
n
o
r
d
er
to
p
r
o
d
u
ce
th
e
ad
ap
ted
g
a
m
e.
T
h
e
g
o
al
o
f
th
e
g
a
m
e
i
s
to
teac
h
k
id
s
h
o
w
to
s
o
lv
e
s
i
m
p
le
eq
u
atio
n
b
y
u
s
i
n
g
a
b
alan
ce
a
n
d
f
r
u
its
,
t
h
e
p
la
y
e
r
w
il
l
h
a
v
e
o
n
e
u
n
k
n
o
w
n
b
a
g
an
d
o
t
h
er
t
y
p
es
o
f
f
r
u
its
,
it
is
a
k
in
d
o
f
r
ep
r
esen
tatio
n
o
f
eq
u
a
tio
n
s
li
k
e:
a
x
+b
=0
.
T
h
e
p
lay
e
r
s
h
o
u
ld
d
r
ag
t
h
e
f
r
u
it
s
f
r
o
m
o
n
e
s
id
e
to
an
o
th
er
u
n
t
il th
e
y
d
ed
u
ce
t
h
e
w
eig
h
t o
f
th
e
u
n
k
n
o
w
n
b
a
g
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
E
C
E
I
SS
N:
2088
-
8708
S
erio
u
s
Ga
mes A
d
a
p
ta
tio
n
A
c
co
r
d
in
g
To
Th
e
Lea
r
n
er’s P
erfo
r
ma
n
ce
s
(
A
min
e
B
ela
h
b
ib
)
453
Fig
u
r
e
1
.
Scr
ee
n
s
h
o
ts
f
r
o
m
th
e
E
QUAFUN
Ser
io
u
s
G
a
m
e
T
h
ese
f
i
g
u
r
es
s
h
o
w
th
e
f
ir
s
t
l
ev
el
w
h
er
e
t
h
e
p
la
y
er
tr
ied
t
w
o
f
r
u
its
,
“
o
r
an
g
e/ap
p
le”,
b
u
t
th
e
g
a
m
e
s
till
u
n
b
alan
ce
d
,
th
e
p
la
y
er
m
o
v
ed
a
w
a
y
t
h
e
ap
p
le
an
d
lef
t
th
e
o
r
an
g
e,
th
i
s
r
esu
l
t
a
co
r
r
ec
t
b
alan
ce
.
T
h
is
w
a
y
th
e
p
la
y
er
k
n
o
w
s
th
a
t
th
e
u
n
k
n
o
w
n
b
ag
co
n
tai
n
s
a
n
o
r
an
g
e,
s
o
h
e
s
h
o
u
ld
d
r
ag
it
to
t
h
e
r
es
u
lt
o
n
t
h
e
b
o
tto
m
o
f
th
e
s
cr
ee
n
.
T
h
e
g
a
m
e
ad
ap
ts
ac
co
r
d
in
g
t
h
ese
b
asic
attr
ib
u
tes
d
ev
id
ed
to
t
w
o
t
y
p
es,
C
o
n
s
tan
t
attr
ib
u
tes
(
Ag
e,
Sex
)
a
n
d
D
y
n
a
m
ic
attr
ib
u
tes
(
Av
er
ag
e
o
f
r
e
s
p
o
n
s
e
ti
m
e,
N
u
m
b
er
o
f
w
r
o
n
g
an
s
w
er
s
,
Nu
m
b
er
o
f
r
ed
u
n
d
a
n
t
f
au
lts
)
.
T
h
ese
attr
ib
u
te
s
ar
e
c
h
o
s
en
ac
co
r
d
in
g
to
t
h
e
g
a
m
ep
la
y
a
n
d
t
y
p
e
o
f
g
a
m
e,
i
n
o
u
r
ca
s
e
w
e
to
o
k
all
th
e
attr
ib
u
tes p
r
esen
t in
t
h
i
s
g
a
m
e.
Th
e
s
aid
a
ttrib
u
tes
ar
e
u
s
ed
in
a
w
a
y
to
ad
a
p
t
an
d
ch
an
g
e
th
e
g
a
m
e
co
n
te
n
t
ac
co
r
d
in
g
to
th
e
p
la
y
er
n
ee
d
s
,
in
o
r
d
er
to
to
m
ak
e
t
h
e
r
elatio
n
b
et
w
ee
n
t
h
e
p
la
y
er
i
n
p
u
t
an
d
t
h
e
g
a
m
e
o
u
tp
u
t,
o
u
r
a
d
ap
ted
g
a
m
e
r
elies
o
n
th
e
s
e
d
ed
u
ce
d
th
r
ee
p
r
o
p
r
eties:
lo
g
ic,
m
e
m
o
r
y
a
n
d
s
p
ee
d
.
T
h
e
d
ed
u
ctio
n
o
f
ea
c
h
p
r
o
p
r
ity
i
s
d
o
n
e
u
s
i
n
g
s
o
m
e
o
f
t
h
e
b
asic a
ttrib
u
te
s
ta
k
en
a
s
en
tr
a
n
ce
w
h
i
le
th
e
p
la
y
er
is
p
lay
in
g
t
h
e
g
a
m
e:
Av
er
a
g
e
o
f
re
s
po
ns
e
t
i
m
e
=
>
Sp
ee
d
I
f
t
h
e
p
la
y
er
i
s
s
lo
w
i
n
r
eso
l
v
in
g
lev
e
ls
w
e
w
i
ll
ad
d
m
o
r
e
allo
w
ed
ti
m
e
i
n
th
e
n
ex
t
le
v
els
b
ef
o
r
e
d
ec
r
ea
s
in
g
it
f
u
r
th
er
i
n
th
e
g
a
m
e
ad
v
a
n
ce
m
e
n
t.
T
he
Nu
m
ber
o
f
w
ro
ng
a
ns
wer
s
=
>
L
o
g
ic
I
f
th
e
p
la
y
er
m
a
k
es
a
lo
t
o
f
er
r
o
r
s
b
ased
o
n
lo
g
ic,
th
e
g
am
e
w
ill
tr
y
to
ad
v
an
ce
s
lo
w
l
y
i
n
lo
g
i
c
d
if
f
ic
u
lt
y
,
ad
d
in
g
o
th
er
p
ar
allel
b
alan
ce
s
.
Nu
m
ber
o
f
re
du
n
da
nt
f
a
ults =>
M
e
m
o
ry
I
f
th
e
p
la
y
er
is
m
a
k
i
n
g
a
lo
t
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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N
:
2
0
8
8
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8708
I
J
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C
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Vo
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7
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Feb
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Fig
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1
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
E
C
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I
SS
N:
2088
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8708
S
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Ga
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p
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To
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“
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3
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ar
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ar
ch
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tectu
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etailed
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.
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u
r
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r
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itect
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1
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1
2
]
,
th
e
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o
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.
3
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4
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k
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lled
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is
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;
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s
g
a
m
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ac
co
r
d
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g
to
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e
v
er
al
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ar
a
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eter
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li
k
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es
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lt
o
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p
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ed
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r
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t
“
ca
lc
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lated
t
h
r
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u
g
h
th
e
n
e
u
r
al
n
et
w
o
r
k
”,
th
e
n
u
m
b
er
o
f
w
r
o
n
g
an
s
w
er
s
,
t
h
e
a
v
er
ag
e
o
f
th
e
ti
m
e
ta
k
en
b
y
t
h
e
lear
n
er
an
d
th
e
n
u
m
b
er
o
f
t
h
e
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ed
u
n
d
an
t
f
a
u
lts
,
all
t
h
es
e
p
ar
am
eter
s
w
il
l
b
u
ild
d
y
n
a
m
icall
y
a
d
ec
is
io
n
th
r
ee
[
1
3
]
.
T
h
e
d
ec
is
io
n
t
r
ee
is
f
o
r
m
a
lis
m
f
o
r
ex
p
r
ess
i
n
g
s
u
c
h
m
ap
p
in
g
s
an
d
co
n
s
i
s
ts
o
f
n
o
d
es
li
n
k
ed
t
o
s
ev
er
al
s
u
b
-
tr
ee
s
an
d
lea
f
s
o
r
d
ec
is
io
n
n
o
d
es lab
eled
w
it
h
a
class
w
h
ich
m
ea
n
s
th
e
d
ec
is
io
n
.
T
h
e
C
4
.
5
[
1
3
]
is
th
e
lear
n
i
n
g
alg
o
r
ith
m
th
at
w
ill
g
e
n
er
ate
t
h
e
th
r
ee
ac
co
r
d
in
g
to
t
h
e
d
ata
s
av
ed
in
t
h
e
d
atab
ase;
th
e
p
r
o
p
o
s
ed
alg
o
r
i
th
m
is
an
e
x
te
n
s
io
n
o
f
I
D3
alg
o
r
ith
m
;
it
b
u
ild
s
d
ec
is
io
n
t
r
ee
s
f
r
o
m
a
s
et
o
f
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ain
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n
g
d
ata
i
n
th
e
s
a
m
e
w
a
y
as
I
D3
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y
u
s
i
n
g
th
e
co
n
ce
p
t
o
f
in
f
o
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m
atio
n
en
tr
o
p
y
,
t
h
e
al
g
o
r
ith
m
o
f
C
4
.
5
f
o
r
b
u
ild
in
g
th
e
d
ec
i
s
io
n
tr
ee
is
d
escr
ib
ed
b
elo
w
:
1
.
C
h
ec
k
f
o
r
b
ase
ca
s
es
2
.
Fo
r
ea
ch
attr
ib
u
te
a:
F
in
d
th
e
n
o
r
m
alize
d
in
f
o
r
m
at
io
n
g
a
in
r
atio
f
r
o
m
s
p
litt
i
n
g
o
n
a.
3
.
L
et
a_
b
est b
e
th
e
attr
ib
u
te
w
it
h
t
h
e
h
i
g
h
est
n
o
r
m
alize
d
i
n
f
o
r
m
atio
n
g
ai
n
.
4
.
C
r
ea
te
a
d
ec
is
io
n
n
o
d
e
th
at
s
p
lits
o
n
a_
b
est.
5
.
R
ec
u
r
o
n
th
e
s
u
b
li
s
ts
o
b
tain
ed
b
y
s
p
litt
in
g
o
n
a_
b
est,
an
d
ad
d
t
h
o
s
e
n
o
d
es a
s
ch
ild
r
en
o
f
n
o
d
e.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
J
E
C
E
Vo
l.
7
,
No
.
1
,
Feb
r
u
ar
y
201
7
:
4
5
1
–
459
456
T
h
e
Fig
u
r
e
4
p
r
esen
t
s
a
n
e
x
a
m
p
le
o
f
th
e
d
ec
is
io
n
tr
ee
g
e
n
e
r
ated
d
y
n
a
m
icall
y
f
r
o
m
t
h
e
d
a
ta
s
av
ed
in
th
e
d
atab
ase
an
d
w
it
h
th
e
u
s
e
o
f
C
4
.
5
lear
n
in
g
al
g
o
r
ith
m
.
T
h
e
a
ttrib
u
tes
“
I
n
p
u
ts
”
th
a
t
f
ee
d
th
e
d
ec
is
io
n
tr
ee
ar
e:
th
e
r
es
u
lt
o
f
th
e
p
r
ed
icto
r
ag
en
t
“c
alcu
lated
th
r
o
u
g
h
t
h
e
n
eu
r
al
n
et
w
o
r
k
,
ac
co
r
d
in
g
to
th
e
lear
n
er
’
s
p
er
f
o
r
m
an
ce
”,
t
h
e
n
u
m
b
er
o
f
w
r
o
n
g
a
n
s
w
er
s
,
t
h
e
av
er
ag
e
o
f
t
h
e
ti
m
e
tak
e
n
b
y
th
e
lear
n
er
an
d
th
e
n
u
m
b
e
r
o
f
th
e
r
ed
u
n
d
an
t
f
a
u
lt
s
.
B
y
co
n
s
t
h
e
clas
s
es
“
O
u
tp
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t
s
”
ar
e:
lo
g
ic,
r
ef
le
x
,
m
e
m
o
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d
s
p
ee
d
Fig
u
r
e
4
.
T
h
e
Dec
is
io
n
T
r
ee
o
f
th
e
D
ec
id
o
r
T
h
e
o
b
tain
ed
r
esu
lts
w
ill
b
e
i
n
ter
p
r
eted
an
d
d
is
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s
s
ed
i
n
t
h
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t
s
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tio
n
,
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o
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alu
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te
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i
m
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ac
t o
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t
h
e
ad
ap
tatio
n
o
f
t
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n
in
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r
o
ce
s
s
th
r
o
u
g
h
s
er
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o
u
s
g
a
m
e
s
.
4.
RE
SU
L
T
AND
DI
SCUS
SI
O
N
T
w
o
v
er
s
io
n
s
o
f
th
e
g
a
m
e
h
a
v
e
b
ee
n
m
ad
e,
t
h
e
o
n
e
t
h
at
p
r
o
v
id
es
a
ll
t
h
e
lev
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s
a
n
d
v
ar
ian
ce
,
an
d
t
h
e
s
ec
o
n
d
g
a
m
e
u
s
i
n
g
th
e
ad
ap
tatio
n
,
w
h
ic
h
tak
e
s
in
to
ac
co
u
n
t
th
e
in
p
u
t
s
in
o
r
d
er
to
a
d
ap
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th
e
p
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o
p
o
s
ed
s
er
io
u
s
g
a
m
e
ac
co
r
d
in
g
l
y
.
T
h
e
s
ec
o
n
d
v
er
s
io
n
is
lear
n
i
n
g
f
r
o
m
t
h
e
p
lay
er
s
a
n
d
h
as
its
o
w
n
lear
n
in
g
p
r
o
ce
s
s
,
th
at
's
w
h
y
w
e
w
ill cl
u
s
ter
t
h
e
p
la
y
er
s
in
to
3
g
r
o
u
p
s
:
a.
Gr
o
u
p
1
: P
lay
i
n
g
n
o
r
m
al
g
a
m
e
(
N=
9
0
)
b.
Gr
o
u
p
2
: P
lay
i
n
g
ad
ap
tiv
e
g
a
m
e(
N=
9
0
)
c.
Gr
o
u
p
3
: P
lay
i
n
g
e
x
p
er
ien
ce
d
ad
ap
tiv
e
g
a
m
e
(
N=
5
0
)
T
h
is
clu
s
ter
i
n
g
s
h
o
u
ld
g
i
v
e
u
s
th
e
b
ig
i
m
ag
e
o
n
w
h
a
t
i
s
t
h
e
i
m
p
ac
t
o
f
t
h
i
s
g
a
m
e
ad
ap
tatio
n
a
n
d
h
o
w
it e
v
o
lv
e
s
b
y
t
h
e
ti
m
e
to
f
it t
h
e
p
lay
er
n
ee
d
s
b
ased
o
n
th
eir
p
r
o
f
ile.
As
m
e
n
tio
n
ed
b
ef
o
r
e
th
e
ad
ap
tatio
n
o
f
th
e
p
r
o
p
o
s
ed
s
er
io
u
s
g
a
m
e
i
s
b
ased
o
n
t
w
o
m
ac
h
in
e
le
ar
n
in
g
alg
o
r
ith
m
s
,
t
h
e
n
eu
r
al
n
et
w
o
r
k
“Ag
en
t
1
”a
n
d
t
h
e
d
ec
i
s
io
n
tr
ee
“Ag
e
n
t
2
”,
t
h
e
f
ir
s
t
o
n
e
w
i
ll
p
r
ed
ict
t
h
e
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n
er
’
s
p
er
f
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m
a
n
ce
d
u
r
i
n
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g
a
m
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eq
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en
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,
b
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n
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th
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o
n
d
o
n
e
w
ill
m
o
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if
y
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r
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r
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lt
g
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v
en
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y
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h
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n
e
u
r
al
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et
w
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k
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n
d
o
th
er
in
f
o
r
m
atio
n
c
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d
u
r
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g
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e
g
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m
e.
Du
r
in
g
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p
ass
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g
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f
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e
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ce
n
e
to
a
n
o
th
er
,
all
t
h
e
co
ll
ec
ted
p
ar
am
eter
s
w
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ll
f
ee
d
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e
p
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ed
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r
ag
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t,
th
is
o
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e
w
ill
f
ee
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d
ec
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n
m
ak
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g
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g
e
n
t
b
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e
p
r
ed
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p
er
f
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m
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n
ce
,
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ter
w
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d
s
t
h
e
d
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i
s
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n
m
ak
in
g
a
g
en
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w
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m
o
d
i
f
y
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e
ch
o
s
en
p
ar
a
m
eter
o
f
“E
q
u
aFu
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g
a
m
e,
ac
co
r
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in
g
to
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is
a
u
to
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ted
m
o
d
i
f
icat
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n
,
th
e
g
a
m
e
w
ill b
e
ad
ap
ted
Fig
u
r
e
5
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
E
C
E
I
SS
N:
2088
-
8708
S
erio
u
s
Ga
mes A
d
a
p
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n
A
c
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d
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To
Th
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Lea
r
n
er’s P
erfo
r
ma
n
ce
s
(
A
min
e
B
ela
h
b
ib
)
457
Fig
u
r
e
5
.
T
h
e
A
d
ap
t
at
io
n
o
f
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e
E
q
u
aFu
n
Ser
io
u
s
Ga
m
e
T
h
e
d
ata
o
b
tain
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a
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ter
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e
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ed
g
a
m
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b
y
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al
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er
s
“
Gr
o
u
p
2
”,
h
av
e
b
ee
n
cu
lt
u
r
ed
in
t
h
r
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ca
teg
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ies
b
y
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s
i
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g
a
E
x
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-
Ma
x
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m
izatio
n
[
1
4
]
alg
o
r
ith
m
,
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al
g
o
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ith
m
o
f
ten
u
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ed
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ca
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ite
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cr
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ab
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ti
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,
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,
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o
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ed
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n
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Fi
g
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r
e
6
.
Fig
u
r
e
6
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ig
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f
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ar
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a
b
le
4
d
etail
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n
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ar
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q
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af
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n
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
J
E
C
E
Vo
l.
7
,
No
.
1
,
Feb
r
u
ar
y
201
7
:
4
5
1
–
459
458
A
v
e
r
a
g
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me
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me
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2
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3
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d
a
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g
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me
2
,
3
4
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3
1
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7
1
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2
As
p
r
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ted
i
n
t
h
e
co
m
p
ar
is
o
n
ab
o
v
e,
th
e
p
ar
a
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ter
s
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av
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b
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k
en
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to
co
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id
er
atio
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ar
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a
v
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s
p
e
n
t
p
er
eq
u
atio
n
av
er
ag
e
o
f
th
e
w
r
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g
a
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r
ig
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t
a
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w
er
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d
th
e
a
v
er
ag
e
o
f
th
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r
ed
u
n
d
an
t
f
au
lts
m
ad
b
y
th
e
lear
n
er
s
”.
T
h
o
s
e
p
ar
am
eter
s
ar
e
d
ec
is
i
v
e
to
m
ea
s
u
r
e
t
h
e
lear
n
er
s
’
p
e
r
f
o
r
m
an
ce
s
,
h
a
v
e
a
g
en
er
al
v
ie
w
o
n
th
eir
i
m
p
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m
en
t,
an
d
h
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an
ac
cu
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ate
co
m
p
ar
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et
w
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t
h
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t
w
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o
f
t
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g
a
m
e.
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h
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o
b
tain
ed
r
esu
lts
s
h
o
w
t
h
at
th
e
ad
ap
ted
g
a
m
e
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s
m
o
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ef
icial
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-
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ar
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g
o
o
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co
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p
ar
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to
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n
o
n
-
ad
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ted
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h
e
f
o
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r
g
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m
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ar
a
m
eter
s
“
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ef
lex
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o
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cr
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ted
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o
r
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eg
ati
v
el
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y
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o
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ite
w
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y
.
A
cc
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in
g
to
th
e
d
ata
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a
v
ed
in
th
e
d
atab
ase
an
d
as
p
r
esen
ted
i
n
t
h
e
F
ig
u
r
e
7
,
t
h
e
p
ar
a
m
eter
t
h
at
h
as
b
ee
n
m
o
r
e
ch
an
g
ed
p
o
s
iti
v
el
y
is
th
e
lo
g
ic
p
ar
a
m
eter
,
t
h
e
n
b
ec
o
m
e
s
p
ee
d
,
r
ef
lex
t
h
e
n
m
e
m
o
r
y
.
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y
co
n
s
t
h
e
p
ar
a
m
ete
r
th
at
h
a
s
b
ee
n
c
h
an
g
ed
n
e
g
a
tiv
el
y
“
Fi
g
u
r
e
8
”
is
lo
g
ic,
s
p
ee
d
,
an
d
r
e
f
le
x
t
h
e
n
m
e
m
o
r
y
.
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h
ic
h
lead
s
to
co
n
clu
d
e,
t
h
at
t
h
e
y
o
u
n
g
lea
r
n
er
s
h
av
e
s
e
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al
d
if
f
ic
u
lt
ies
w
ith
lo
g
ica
l
o
p
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atio
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s
a
g
ai
n
s
t
t
h
e
y
d
o
n
’
t
h
a
v
e
d
if
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icu
lties
w
it
h
m
e
m
o
r
izat
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n
t
h
an
k
s
to
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h
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f
asti
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g
a
g
e.
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r
t
h
is
r
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s
o
n
e
x
p
er
ts
an
d
p
ed
ag
o
g
u
es
m
u
s
t
t
h
in
k
h
o
w
to
i
m
p
r
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v
e
th
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lo
g
ic
al
r
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s
o
n
i
n
g
o
f
t
h
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s
k
in
d
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tr
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ci
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g
m
o
r
e
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m
a
n
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er
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Fig
u
r
e
7
.
P
ie
ch
ar
t o
f
th
e
P
o
s
tiv
e
A
d
ap
tatio
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P
ar
em
eter
s
Fig
u
r
e
8
.
P
ie
ch
ar
t o
f
th
e
N
e
g
ativ
e
A
d
ap
tatio
n
o
f
P
ar
em
eter
s
T
h
e
co
m
p
ar
is
o
n
o
f
t
h
e
r
esu
lts
o
b
tain
ed
b
y
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p
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p
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s
ed
s
er
io
u
s
g
a
m
e
w
i
th
a
s
i
m
ilar
g
a
m
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[
1
5
]
th
at
teac
h
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ar
it
h
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etic
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asic
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at
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en
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et
w
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ar
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ar
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eter
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ir
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c,
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p
ee
d
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d
m
e
m
o
r
y
.
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y
co
n
s
t
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d
y
n
a
m
ic
d
if
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ic
u
lt
y
w
il
l
b
e
ch
an
g
ed
i
n
t
h
e
s
ec
o
n
d
o
n
e.
T
h
e
ad
ap
tatio
n
b
ased
o
n
th
e
lear
n
e
r
s
’
p
er
f
o
r
m
an
ce
s
h
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s
p
r
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v
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it
s
s
u
cc
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s
,
ac
co
r
d
in
g
to
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e
o
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tain
ed
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esu
lts
o
f
b
o
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lear
n
in
g
a
n
al
y
tics
o
r
th
e
co
m
p
ar
is
o
n
o
f
t
h
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to
w
v
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s
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p
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p
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s
ed
g
a
m
e.
Gen
er
all
y
th
e
p
r
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ce
s
s
o
f
ad
ap
tatio
n
ad
o
p
ted
in
th
eir
p
ap
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,
allo
w
s
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u
d
en
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s
to
ex
p
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ce
t
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g
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m
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s
,
ea
ch
o
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e
ac
co
r
d
in
g
to
h
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s
le
v
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e
v
er
y
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x
p
er
ien
ce
i
s
d
if
f
er
en
t
f
r
o
m
o
th
er
s
;
w
h
ic
h
m
a
k
e
it a
f
le
x
ib
le
a
n
d
b
en
ef
icial
g
a
m
e
f
o
r
in
telli
g
e
n
t le
ar
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i
n
g
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
E
C
E
I
SS
N:
2088
-
8708
S
erio
u
s
Ga
mes A
d
a
p
ta
tio
n
A
c
co
r
d
in
g
To
Th
e
Lea
r
n
er’s P
erfo
r
ma
n
ce
s
(
A
min
e
B
ela
h
b
ib
)
45
9
5.
CO
NCLU
SI
O
N
T
h
e
i
m
p
o
r
tan
t
r
o
le
th
at
p
la
y
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u
s
g
a
m
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s
i
n
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e
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r
n
in
g
p
r
o
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s
s
to
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m
p
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o
v
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t
h
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lean
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g
ca
p
ab
ilit
ies
o
f
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h
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an
d
allo
w
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e
m
to
lear
n
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e
w
k
n
o
w
led
g
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a
n
d
s
k
ill
s
;
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g
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n
d
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to
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v
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a
t
w
ill
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ak
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m
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o
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b
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f
icial;
a
m
o
n
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tec
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iq
u
es t
h
er
e
is
t
h
e
a
d
ap
tatio
n
p
r
o
ce
s
s
th
at
h
a
s
b
ee
n
d
etailed
in
t
h
is
p
ap
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.
As
m
en
tio
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ed
b
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o
r
e,
t
h
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p
r
o
ce
s
s
o
f
ad
ap
tatio
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b
ased
o
n
th
e
lear
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p
er
f
o
r
m
a
n
ce
ca
n
ad
ap
t
a
v
ar
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y
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f
g
a
m
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p
ar
a
m
eter
s
,
i
n
o
r
d
er
to
,
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m
p
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o
v
e
lear
n
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s
’
ab
ilit
ies
to
lear
n
w
i
th
o
u
t
t
h
e
in
ter
ac
tio
n
o
f
t
h
e
in
s
tr
u
cto
r
s
.
A
cc
o
r
d
in
g
to
th
e
o
b
tain
ed
r
esu
lts
o
f
th
e
co
n
ce
p
t
ad
o
p
te
d
in
th
is
p
ap
er
h
as
allo
w
ed
r
eso
lu
tio
n
o
f
s
ev
er
al
is
s
u
es
e
n
co
u
n
ter
ed
b
y
th
e
y
o
u
n
g
lear
n
er
s
to
r
eso
l
v
e
m
at
h
e
m
a
tical
eq
u
atio
n
s
.
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h
e
p
r
o
p
o
s
ed
p
r
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ce
s
s
o
f
ad
ap
tatio
n
ca
n
b
e
u
s
ed
also
to
ad
ap
t
th
e
ass
ess
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[1
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S
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.
[2
]
W
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ters
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P
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J.M
.
,
V
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r
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p
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E.
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p
,
H.
(2
0
1
1
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M
e
a
su
rin
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g
in
se
rio
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s
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m
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s: a ca
se
.
[3
]
W
a
lk
e
r,
J.
(2
0
0
9
)
L
e
f
t
4
De
a
d
2
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Ex
c
lu
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Ha
n
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P
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w
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Ro
c
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P
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h
o
tg
u
n
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P
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G
a
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in
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sin
c
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1
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3
.
On
li
n
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a
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le:
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t
tp
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/www
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ro
c
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[4
]
Bra
th
w
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B.
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n
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I.
(
2
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h
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Bo
sto
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M
A
:
Ch
a
rles
Riv
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d
ia.
[5
]
Ba
k
k
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s,
S
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S
p
ro
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P
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J.
(2
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Ra
p
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A
I.
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Co
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A
I
in
G
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1
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3
-
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0
4
.
[6
]
Ro
b
e
rts,
D.L
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a
n
d
Isb
e
ll
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C.
L
.
(2
0
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A
su
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tativ
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In
t.
T
ra
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c
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A
p
p
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3
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,
6
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.
[7
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Nie
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J.
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Ried
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M
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O
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(2
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train
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latio
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I
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P
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W
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G
a
m
e
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Brig
h
to
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UK
(
p
p
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8
9
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9
8
).
[8
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Ch
risto
p
h
Klimm
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rist
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2
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d
V
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G
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En
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m
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t.
[9
]
S
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Ba
k
k
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s,
P
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p
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Ja
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A
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V
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a
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A
I.
[1
0
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JA
V
A
A
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De
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F
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:
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tt
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:
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).
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2
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3
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Qu
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J.R.
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4
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De
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A
.
P
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;
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a
ird
,
N.
M
.
;
R
u
b
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,
D.B.
(
1
9
7
7
).
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M
a
x
im
u
m
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In
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3
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–
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8
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JST
OR 2
9
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.
[1
5
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Jo
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T
re
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Bru
n
o
B
o
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b
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A
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M
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ECHAN
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:
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a
k
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s
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a
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s
p
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y
a
b
le
a
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d
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,
Un
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d
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Qu
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c
à
Ch
ic
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ti
m
i,
(Qu
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g
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d
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d
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s,
2
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3
)
Ca
n
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d
a
5
5
5
b
o
u
l.
U
n
iv
e
rsité,
G
7
H 2
B1
.
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