Models of consensus are used to manage multiple agent systems in order to
choose between different recommendations provided by the system. It is assumed
that there is a central agent that solicits recommendations or plans from other
agents. That agent the n determines the consensus of the other agents, and
chooses the resultant consensus recommendation or plan. Voting schemes such as
this have been used in a variety of domains, including air traffic control.
This paper uses an analytic model to study the use of consensus in multiple
agent systems. The binomial model is used to study the probability that the
consensus judgment is correct or incorrect. That basic model is extended to
account for both different levels of agent competence and unequal prior odds.
The analysis of that model is critical in the investigation of multiple agent
systems, since the model leads us to conclude that in some cases consensus
judgment is not appropriate. In addition, the results allow us to determine how
many agents should be used to develop consensus decisions, which agents should
be used to develop consensus decisions and under which conditions the consensus
model should be used.Comment: Appears in Proceedings of the Tenth Conference on Uncertainty in
Artificial Intelligence (UAI1994