Constraint satisfaction has been a very successful paradigm for
solving problems such as resource allocation and planning. Many of
these problems pose themselves in a context involving multiple
agents,
and protecting privacy of information among them is often
desirable.
Secure multiparty computation (SMC) provides methods that in
principle
allow such computation without leaking any information. However,
it
does not consider the issue of keeping agents' decisions private
from
one another. In this paper, we show an algorithm that uses SMC in
distributed computation to satisfy this objective.