Tolerable Manipulability in Dynamic Assignment without Money

We study a problem of dynamic allocation without money. Agents have arrivals and departures and strict preferences over items. Strategyproofness requires the use of an arrival-priority serial-dictatorship (APSD) mechanism, which is ex post Pareto efficient but has poor {\em ex ante} efficiency as measured through average rank efficiency. We introduce the {\em scoring-rule} (SR) mechanism, which biases in favor of allocating items that an agent values above the population consensus. The SR mechanism is not strategyproof but has tolerable manipulability in the sense that: (i) if every agent optimally manipulates, it reduces to APSD, and (ii) it significantly outperforms APSD for rank efficiency when only a fraction of agents are strategic. The performance of SR is also robust to mistakes by agents that manipulate on the basis of inaccurate information about the popularity of items.

• Type: Conference
• Year: 2010
• Where: AAAI Conference on Artificial Intelligence (AAAI'10),
• Authors: James Zou, Sujit Gujar, and David C. Parkes
• Keywords: AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE (AAAI'10), 2010, Allocation Mechanism, Tolerable Manipulability