The Clarke tax as a consensus mechanism among automated agents

TLDR

In distributed AI, autonomous agents must reach consensus, traditionally via negotiation or voting mechanisms, but a non‑manipulable choice mechanism like the Clarke tax—though theoretically attractive—faces practical implementation challenges. The paper investigates using the Clarke tax as an effective preference‑revealing mechanism for automated agents to reduce explicit negotiation. The authors propose employing the Clarke tax as a preference‑revealing mechanism for automated agents, thereby minimizing explicit negotiation.

Abstract

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.