{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T16:34:03Z","timestamp":1782405243094,"version":"3.54.5"},"reference-count":47,"publisher":"Association for Computing Machinery (ACM)","issue":"2","license":[{"start":{"date-parts":[[2017,2,24]],"date-time":"2017-02-24T00:00:00Z","timestamp":1487894400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["SIGecom Exch."],"published-print":{"date-parts":[[2017,2,24]]},"abstract":"<jats:p>\n            <jats:italic>Information structure design<\/jats:italic>\n            , also sometimes known as\n            <jats:italic>signaling<\/jats:italic>\n            or\n            <jats:italic>persuasion<\/jats:italic>\n            , is concerned with understanding the effects of information on the outcomes of strategic interactions (the descriptive question), and in characterizing and computing the information sharing strategies which optimize some design objective (the prescriptive question). Both questions are illuminated through the lens of algorithms and complexity, as evidenced by recent work on the topic in the algorithmic game theory community. This monograph is a biased survey of this work, and paints a picture of the current state of progress and challenges ahead.\n          <\/jats:p>\n          <jats:p>\n            We divide information structure design into\n            <jats:italic>single agent<\/jats:italic>\n            and\n            <jats:italic>multiple agent<\/jats:italic>\n            models, and further subdivide the multiple agent case into the\n            <jats:italic>public channel<\/jats:italic>\n            and\n            <jats:italic>private channel<\/jats:italic>\n            modes of information revelation. In each of these three cases, we describe the most prominent models and applications, survey the associated algorithms and complexity results and their structural implications, and outline directions for future work.\n          <\/jats:p>","DOI":"10.1145\/3055589.3055591","type":"journal-article","created":{"date-parts":[[2017,2,27]],"date-time":"2017-02-27T13:06:52Z","timestamp":1488200812000},"page":"2-24","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":46,"title":["Algorithmic information structure design"],"prefix":"10.1145","volume":"15","author":[{"given":"Shaddin","family":"Dughmi","sequence":"first","affiliation":[{"name":"University of Southern California"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2017,2,24]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/2229012.2229017"},{"key":"e_1_2_1_2_1","unstructured":"Alonso R. and Camara O. 2014. Bayesian persuasion with heterogeneous priors. Available at SSRN 2306820.  Alonso R. and Camara O. 2014. Bayesian persuasion with heterogeneous priors. Available at SSRN 2306820 ."},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1257\/aer.20140737"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.geb.2016.10.009"},{"key":"e_1_2_1_5_1","first-page":"1","article-title":"Persuasion is now 30 per cent of us gdp","volume":"1","author":"Antioch G.","year":"2013","journal-title":"Economic Roundup"},{"key":"e_1_2_1_6_1","doi-asserted-by":"crossref","unstructured":"Arieli I. and Babichenko Y. 2016. Private bayesian persuasion. Available at SSRN 2721307.  Arieli I. and Babichenko Y. 2016. Private bayesian persuasion. Available at SSRN 2721307 .","DOI":"10.2139\/ssrn.2721307"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/2558397"},{"key":"e_1_2_1_8_1","unstructured":"Babichenko Y. and Barman S. 2016. Computational aspects of private bayesian persuasion. arXiv preprint arXiv:1603.01444.  Babichenko Y. and Barman S. 2016. Computational aspects of private bayesian persuasion. arXiv preprint arXiv:1603.01444 ."},{"key":"e_1_2_1_9_1","unstructured":"Bardhi A. and Guo Y. 2016. Modes of persuasion toward unanimous consent. Manuscript.  Bardhi A. and Guo Y. 2016. Modes of persuasion toward unanimous consent. Manuscript ."},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1257\/aer.20130848"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.3982\/TE1808"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/2940716.2940753"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00199-006-0080-z"},{"key":"e_1_2_1_14_1","first-page":"4","article-title":"Implementation of Reduced Form Auctions","volume":"59","author":"Border K. C.","year":"1991","journal-title":"A Geometric Approach. Econometrica"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/2229012.2229033"},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.0741-6261.2007.00119.x"},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/2213977.2214021"},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.5555\/2805184.2805190"},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/FOCS.2015.91"},{"key":"e_1_2_1_20_1","unstructured":"Cheng Y. and Xu H. 2016. personal communication.  Cheng Y. and Xu H. 2016. personal communication."},{"key":"e_1_2_1_21_1","volume-title":"Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence. AAAI Press, 632--637","author":"Conitzer V."},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.2307\/1913390"},{"key":"e_1_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/FOCS.2014.45"},{"key":"e_1_2_1_25_1","volume-title":"Proceedings of the 25th ACM Symposium on Discrete Algorithms (SODA).","author":"Dughmi S."},{"key":"e_1_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/2940716.2940781"},{"key":"e_1_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/2897518.2897583"},{"key":"e_1_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/2229012.2229051"},{"key":"e_1_2_1_29_1","doi-asserted-by":"crossref","unstructured":"Gick W. and Pausch T. 2012. Persuasion by stress testing: Optimal disclosure of supervisory information in the banking sector. Number 32\/2012. Discussion Paper Deutsche Bundesbank.  Gick W. and Pausch T. 2012. Persuasion by stress testing: Optimal disclosure of supervisory information in the banking sector . Number 32\/2012. Discussion Paper Deutsche Bundesbank.","DOI":"10.2139\/ssrn.2796887"},{"key":"e_1_2_1_30_1","doi-asserted-by":"crossref","unstructured":"Goldstein I. and Leitner Y. 2013. Stress tests and information disclosure. FRB of Philadelphia Working Paper.  Goldstein I. and Leitner Y. 2013. Stress tests and information disclosure . FRB of Philadelphia Working Paper.","DOI":"10.21799\/frbp.wp.2013.26"},{"key":"e_1_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/2764468.2764538"},{"key":"e_1_2_1_32_1","volume-title":"Proceedings of the Twenty-Third international joint conference on Artificial Intelligence. AAAI Press, 157--163","author":"Guo M."},{"key":"e_1_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1257\/aer.101.6.2590"},{"key":"e_1_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.geb.2015.02.006"},{"key":"e_1_2_1_35_1","doi-asserted-by":"crossref","unstructured":"Kolotilin A. Li M. Mylovanov T. and Zapechelnyuk A. 2015. Persuasion of a privately informed receiver. Tech. rep. Working paper.  Kolotilin A. Li M. Mylovanov T. and Zapechelnyuk A. 2015. Persuasion of a privately informed receiver. Tech. rep. Working paper.","DOI":"10.2139\/ssrn.2913916"},{"key":"e_1_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1086\/676597"},{"key":"e_1_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/2764468.2764508"},{"key":"e_1_2_1_38_1","first-page":"191","article-title":"One quarter of gdp is persuasion","volume":"85","author":"McCloskey D.","year":"1995","journal-title":"The American Economic Review"},{"key":"e_1_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1287\/moor.6.1.58"},{"key":"e_1_2_1_40_1","doi-asserted-by":"crossref","unstructured":"Nisan N. Roughgarden T. Tardos E. and Vazirani V. V. 2007. Algorithmic Game Theory. Cambridge University Press New York NY USA.   Nisan N. Roughgarden T. Tardos E. and Vazirani V. V. 2007. Algorithmic Game Theory . 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Manuscript ."},{"key":"e_1_2_1_47_1","volume-title":"AAAI Conference on Artificial Intelligence (AAAI).","author":"Xu H."},{"key":"e_1_2_1_48_1","volume-title":"AAAI Conference on Artificial Intelligence (AAAI).","author":"Xu H."}],"container-title":["ACM SIGecom Exchanges"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3055589.3055591","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3055589.3055591","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T03:36:20Z","timestamp":1750217780000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3055589.3055591"}},"subtitle":["a survey"],"short-title":[],"issued":{"date-parts":[[2017,2,24]]},"references-count":47,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2017,2,24]]}},"alternative-id":["10.1145\/3055589.3055591"],"URL":"https:\/\/doi.org\/10.1145\/3055589.3055591","relation":{},"ISSN":["1551-9031"],"issn-type":[{"value":"1551-9031","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,2,24]]},"assertion":[{"value":"2017-02-24","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}