{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/a-cost-effective-framework-for-preference","title":"A Cost-Effective Framework for Preference Elicitation and Aggregation","arxiv_id":"1805.05287","date":"2018-05-14","proceeding":null,"authors":["Zhibing Zhao","Haoming Li","Junming Wang","Jeffrey Kephart","Nicholas Mattei","Hui Su","Lirong Xia"],"abstract":"We propose a cost-effective framework for preference elicitation and\naggregation under the Plackett-Luce model with features. Given a budget, our\nframework iteratively computes the most cost-effective elicitation questions in\norder to help the agents make a better group decision.\n  We illustrate the viability of the framework with experiments on Amazon\nMechanical Turk, which we use to estimate the cost of answering different types\nof elicitation questions. We compare the prediction accuracy of our framework\nwhen adopting various information criteria that evaluate the expected\ninformation gain from a question. Our experiments show carefully designed\ninformation criteria are much more efficient, i.e., they arrive at the correct\nanswer using fewer queries, than randomly asking questions given the budget\nconstraint.","url_abs":"http://arxiv.org/abs/1805.05287v2","url_pdf":"http://arxiv.org/pdf/1805.05287v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"a-cost-effective-framework-for-preference","repo_url":"https://github.com/haoming-codes/preference-mpc","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"GPL-3.0"}}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1805.05287","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}