{"type":"ScholarlyArticle","title":"Mechanism Design with Partial Revelation","authors":[{"name":"Nathanael Hyafil","slug":"nathanael-hyafil","given":"Nathanael","family":"Hyafil","affiliation":""},{"name":"Craig Boutilier","slug":"craig-boutilier","given":"Craig","family":"Boutilier","affiliation":""}],"abstract":"Classic direct mechanisms require full utility revelation from agents, which can be very difficult in practical multi-attribute settings. In this work, we study partial revelation within the framework of one-shot mechanisms. Each agent's type space is partitioned into a finite set of partial types and agents (should) report the partial type within which their full type lies. A classic result 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 mechanisms with worst-case guarantees on both manipulability and efficiency.","doi":null,"url":"https://ijcai.org/proceedings/2007/215","pdf":"https://ijcai.org/proceedings/2007/0215.pdf","markdown":"https://ijcai.org/proceedings/2007/215.md","bibtex":"https://ijcai.org/proceedings/2007/bibtex/215","volume":{"slug":"2007","title":"Proceedings of the Twentieth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2007","url":"https://ijcai.org/proceedings/2007/","year":2007,"location":"Hyderabad, India","dates":"","editors":"Ramon López de Mántaras","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":215,"pages":{"first":1333,"last":1339},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}