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.