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Ta b l e 2 .
(a) The individual welfare function,
w
X
i
,
i
=1
,
2
,
3, and (b) the group welfare function
w
X
1
X
2
X
3
(
a
11
,a
22
,a
33
)
(b)
(
a
22
,a
33
)
a
11
(
D,R
)(
D,G
)(
F,R
)(
F,G
)
C
0.023
(a)
w
X
1
(
C
)=05
w
X
1
(
S
)=0
.
5
w
X
2
(
D
)=0
.
49
w
X
2
(
F
)=0
.
51
0.207
0.081
0.189
w
X
3
(
R
) = 0426
w
X
3
(
G
)=0
.
574
S
0.130
0.130
0.192
0.048
6
Conclusions
As acknowledged by many decision theorists [2,10,16], neoclassical game theory is an
appropriate model for competitive and market-driven scenarios, but it offers limited ca-
pacity for the design and synthesis of multiagent systems that are intended to cooperate,
compromise, and negotiate.
This paper (i) presents a principle-based extension to neoclassical game theory that
replaces categorical utilities with conditional utilities that encode the social influence
relationships that exist among the agents; (ii) develops notions of rational multiagent
decision making to define rational behavior simultaneously for groups and for individ-
uals; and (iii) addresses computational complexity by maximally exploiting influence
sparseness among the agents. Conditional game theory provides a powerful framework
within which to design and synthesize cooperative multiagent systems.
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