The Clarke Tax as a Consensus Mechanism Among Automated Agents

Eithan Ephrati, Jeffrey S. Rosenschein

When autonomous agents attempt to coordinate action, it is often necessary that they reach some kind of consensus. Reaching such a consensus has traditionally been dealt with in the Distributed Artificial Intelligence literature via the mechanism of negotiation. Another alternative is to have agents bypass negotiation by using a voting mechanism; each agent expresses its preferences, and a group choice mechanism is used to select the result. Some choice mechanisms are better than others, and ideally we would like one that cannot be manipulated by an untruthful agent. One such non-manipulable choice mechanism is the Clarke tax [Clarke, 1971]. Though theoretically attractive, the Clarke tax presents a number of difficulties when one attempts to use it in a practical implementation. This paper examines how the Clarke tax could be used as an effective "preference revealer" in the domain of automated agents, reducing the need for explicit negotiation.


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