{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,7]],"date-time":"2024-08-07T07:34:43Z","timestamp":1723016083991},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,8]]},"abstract":"<jats:p>We study the classic public project problem, where a group of agents need to decide whether or not to build a non-excludable public project.\u00a0 We focus on efficient, strategy-proof, and weakly budget-balanced mechanisms (VCG redistribution mechanisms). Our aim is to maximize the worst-case efficiency ratio --- the worst-case ratio between the achieved total utility and the first-best maximum total utility. Previous studies have identified the optimal mechanism for 3 agents.\u00a0 It was also conjectured that the worst-case efficiency ratio approaches 1 asymptotically as the number of agents approaches infinity.\u00a0 Unfortunately, no optimal mechanisms have been identified for cases with more than 3 agents. We propose an asymptotically optimal mechanism, which achieves a worst-case efficiency ratio of 1, under a minor technical assumption: we assume the agents' valuations are rational numbers with bounded denominators.\u00a0 We also show that if the agents' valuations are drawn from identical and independent distributions, our mechanism's efficiency ratio equals 1 with probability approaching 1 asymptotically.\u00a0 Our results significantly improve on previous results. The best previously known asymptotic worst-case efficiency ratio is 0.102.\u00a0 For non-asymptotic cases, our mechanisms also achieve better ratios than all previous results.\u00a0\u00a0<\/jats:p>","DOI":"10.24963\/ijcai.2019\/45","type":"proceedings-article","created":{"date-parts":[[2019,7,28]],"date-time":"2019-07-28T07:46:05Z","timestamp":1564299965000},"page":"315-321","source":"Crossref","is-referenced-by-count":1,"title":["An Asymptotically Optimal VCG Redistribution Mechanism for the Public Project Problem"],"prefix":"10.24963","author":[{"given":"Mingyu","family":"Guo","sequence":"first","affiliation":[{"name":"School of Computer Science, University of Adelaide, Australia"}]}],"member":"10584","event":{"number":"28","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"acronym":"IJCAI-2019","name":"Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}","start":{"date-parts":[[2019,8,10]]},"theme":"Artificial Intelligence","location":"Macao, China","end":{"date-parts":[[2019,8,16]]}},"container-title":["Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2019,7,28]],"date-time":"2019-07-28T07:46:26Z","timestamp":1564299986000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2019\/45"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2019,8]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2019\/45","relation":{},"subject":[],"published":{"date-parts":[[2019,8]]}}}