{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,7]],"date-time":"2024-08-07T07:40:30Z","timestamp":1723016430948},"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>Incentives are explored in the sharing economy to inspire users for better resource allocation. Previous works build a budget-feasible incentive mechanism to learn users' cost distribution. However, they only consider a special case that all tasks are considered as the same. The general problem asks for finding a solution when the cost for different tasks varies. In this paper, we investigate this general problem by considering a system with k levels of difficulty. We present two incentivizing strategies for offline and online implementation, and formally derive the ratio of utility between them in different scenarios. We propose a regret-minimizing mechanism to decide incentives by dynamically adjusting budget assignment and learning from users' cost distributions. Our experiment demonstrates utility improvement about 7 times and time saving of 54% to meet a utility objective compared to the previous works.<\/jats:p>","DOI":"10.24963\/ijcai.2019\/94","type":"proceedings-article","created":{"date-parts":[[2019,7,28]],"date-time":"2019-07-28T03:46:05Z","timestamp":1564285565000},"page":"665-671","source":"Crossref","is-referenced-by-count":4,"title":["Explore Truthful Incentives for Tasks with Heterogenous Levels of Difficulty in the Sharing Economy"],"prefix":"10.24963","author":[{"given":"Pengzhan","family":"Zhou","sequence":"first","affiliation":[{"name":"Dept. of Electrical and Computer Engineering, Stony Brook University, Stony Brook, NY 11794, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin","family":"Wei","sequence":"additional","affiliation":[{"name":"Dept. of Computer Science, Old Dominion University, Norfolk, VA 23529, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cong","family":"Wang","sequence":"additional","affiliation":[{"name":"Dept. of Computer Science, Old Dominion University, Norfolk, VA 23529, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuanyuan","family":"Yang","sequence":"additional","affiliation":[{"name":"Dept. of Electrical and Computer Engineering, Stony Brook University, Stony Brook, NY 11794, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"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":"2019-07-28T03:46:44Z","timestamp":1564285604000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2019\/94"}},"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\/94","relation":{},"subject":[],"published":{"date-parts":[[2019,8]]}}}