Mechanism design studies how to design mechanisms that result in good outcomes even when agents strategically report their preferences. In traditional settings, it is assumed that a mechanism can enforce payments to give an incentive for agents to act honestly. However, in many Internet application domains, introducing monetary transfers is impossible or undesirable. Also, in such highly anonymous settings as the Internet, declaring preferences dishonestly is not the only way to manipulate the mechanism. Often, it is possible for an agent to pretend to be multiple agents and submit multiple reports under different identifiers, e.g., by creating different e-mail addresses. The effect of such false-name manipulations can be more serious in a mechanism without monetary transfers, since submitting multiple reports would have no risk. In this paper, we present a case study in false-name- proof mechanism design without money. In our basic setting, agents are located on a real line, and the mechanism must select the location of a public facility; the cost of an agent is its distance to the facility. This setting is called the facility location problem and can represent various sit-uations where an agent's preference is single-peaked. First, we fully characterize the deterministic false-name-proof facility location mechanisms in this basic setting. By utilizing this characterization, we show the tight bounds of the approximation ratios for two objective functions: social cost and maximum cost. We then extend the results in two natural directions: A domain where a mechanism can be randomized and a domain where agents are located in a tree. Furthermore, we clarify the connections between false-name- proofness and other related properties.
|出版ステータス||出版済み - 1 1 2011|
|イベント||10th International Conference on Autonomous Agents and Multiagent Systems 2011, AAMAS 2011 - Taipei, 台湾省、中華民国|
継続期間: 5 2 2011 → 5 6 2011
|その他||10th International Conference on Autonomous Agents and Multiagent Systems 2011, AAMAS 2011|
|Period||5/2/11 → 5/6/11|
All Science Journal Classification (ASJC) codes
- Artificial Intelligence