Mechanism Design with Partial Revelation

Classic direct mechanisms require full type (or utility) revelation from participating agents, something that can be very difficult in practical multi-attribute settings. In this work, we study partial revelation within the framework of oneshot (i.e., non-sequential) mechanisms. Each agent’s type space is partitioned into a finite set of partial types and agent’s (should) report the partial type within which their full type lies. A classic result of Roberts implies that implementation in dominant strategies is impossible in this model. We first show that a relaxation to Bayes-Nash implementation does not circumvent the problem. We then propose a class of partial revelation mechanisms that achieve approximate dominant strategy implementation, and describe a computationally tractable algorithm for myopically optimizing the partitioning of each agent’s type space to reduce manipulability and social welfare loss. This allows for the automated design of one-shot partial revelation...

• Type: Conference
• Year: 2007
• Where: IJCAI
• Authors: Nathanael Hyafil, Craig Boutilier
• Keywords: Agent’s Type Space, Artificial Intelligence, IJCAI 2007, Partial Revelation, Partial Revelation Mechanisms