AI surpasses humans at six-player poker
Self-learning Pluribus beats five humans in Texas hold'em showdown Superhuman performance by artificial intelligence (AI) has been demonstrated in two-player, deterministic, zero-sum, perfect-information games ( 1 ) such as chess, checkers ( 2 ), Hex, and Go ( 3 ). Research using AI has broaden...
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| Veröffentlicht in: | Science (American Association for the Advancement of Science) 2019-08, Vol.365 (6456), p.864-865 |
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| creator | Blair, Alan Saffidine, Abdallah |
| description | Self-learning Pluribus beats five humans in Texas hold'em showdown
Superhuman performance by artificial intelligence (AI) has been demonstrated in two-player, deterministic, zero-sum, perfect-information games (
1
) such as chess, checkers (
2
), Hex, and Go (
3
). Research using AI has broadened to include games with challenging attributes such as randomness, multiple players, or imperfect information. Randomness is a feature of dice games, and card games include the additional complexity that each player sees some cards that are hidden from others. These aspects more closely resemble real-world situations, and this research may thus lead to algorithms with wider applicability. On page 885 of this issue, Brown and Sandholm (
4
) show that a new computer player called Pluribus exceeds human performance for six-player Texas hold'em poker. |
| doi_str_mv | 10.1126/science.aay7774 |
| format | Article |
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Superhuman performance by artificial intelligence (AI) has been demonstrated in two-player, deterministic, zero-sum, perfect-information games (
1
) such as chess, checkers (
2
), Hex, and Go (
3
). Research using AI has broadened to include games with challenging attributes such as randomness, multiple players, or imperfect information. Randomness is a feature of dice games, and card games include the additional complexity that each player sees some cards that are hidden from others. These aspects more closely resemble real-world situations, and this research may thus lead to algorithms with wider applicability. On page 885 of this issue, Brown and Sandholm (
4
) show that a new computer player called Pluribus exceeds human performance for six-player Texas hold'em poker.</description><identifier>ISSN: 0036-8075</identifier><identifier>EISSN: 1095-9203</identifier><identifier>DOI: 10.1126/science.aay7774</identifier><identifier>PMID: 31467208</identifier><language>eng</language><publisher>United States: American Association for the Advancement of Science</publisher><subject>Algorithms ; Artificial intelligence ; Card games ; Checkers ; Chess ; Human performance ; PERSPECTIVES ; Randomness</subject><ispartof>Science (American Association for the Advancement of Science), 2019-08, Vol.365 (6456), p.864-865</ispartof><rights>Copyright © 2019, American Association for the Advancement of Science</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c413t-17233ab65a07836a28f4c6cc3589e285f4850067ab8932f812d74a4d69a421703</citedby><cites>FETCH-LOGICAL-c413t-17233ab65a07836a28f4c6cc3589e285f4850067ab8932f812d74a4d69a421703</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,2884,2885,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31467208$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Blair, Alan</creatorcontrib><creatorcontrib>Saffidine, Abdallah</creatorcontrib><title>AI surpasses humans at six-player poker</title><title>Science (American Association for the Advancement of Science)</title><addtitle>Science</addtitle><description>Self-learning Pluribus beats five humans in Texas hold'em showdown
Superhuman performance by artificial intelligence (AI) has been demonstrated in two-player, deterministic, zero-sum, perfect-information games (
1
) such as chess, checkers (
2
), Hex, and Go (
3
). Research using AI has broadened to include games with challenging attributes such as randomness, multiple players, or imperfect information. Randomness is a feature of dice games, and card games include the additional complexity that each player sees some cards that are hidden from others. These aspects more closely resemble real-world situations, and this research may thus lead to algorithms with wider applicability. On page 885 of this issue, Brown and Sandholm (
4
) show that a new computer player called Pluribus exceeds human performance for six-player Texas hold'em poker.</description><subject>Algorithms</subject><subject>Artificial intelligence</subject><subject>Card games</subject><subject>Checkers</subject><subject>Chess</subject><subject>Human performance</subject><subject>PERSPECTIVES</subject><subject>Randomness</subject><issn>0036-8075</issn><issn>1095-9203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><recordid>eNpdkLtOw0AQRVcIREKgpgJZooDGyezDu-syinhEikQDtTXZrIWDX-zEEvl7HMVQUE1xz1zNHMauOUw5F3pGrvC181PEvTFGnbAxhzSJUwHylI0BpI4tmGTELoi2AH2WynM2klxpI8CO2f18GVEXWiTyFH10FdYU4S6i4jtuS9z7ELXNpw-X7CzHkvzVMCfs_enxbfESr16fl4v5KnaKy13MjZAS1zpBMFZqFDZXTjsnE5t6YZNc2QRAG1zbVIrccrExCtVGp6gENyAn7OHY24bmq_O0y6qCnC9LrH3TUSaElf2LqRU9evcP3TZdqPvrDpTQ1nI4FM6OlAsNUfB51oaiwrDPOGQHh9ngMBsc9hu3Q2-3rvzmj_-V1gM3R2BLuyb85UKb_irN5Q8eInU_</recordid><startdate>20190830</startdate><enddate>20190830</enddate><creator>Blair, Alan</creator><creator>Saffidine, Abdallah</creator><general>American Association for the Advancement of Science</general><general>The American Association for the Advancement of Science</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QF</scope><scope>7QG</scope><scope>7QL</scope><scope>7QP</scope><scope>7QQ</scope><scope>7QR</scope><scope>7SC</scope><scope>7SE</scope><scope>7SN</scope><scope>7SP</scope><scope>7SR</scope><scope>7SS</scope><scope>7T7</scope><scope>7TA</scope><scope>7TB</scope><scope>7TK</scope><scope>7TM</scope><scope>7U5</scope><scope>7U9</scope><scope>8BQ</scope><scope>8FD</scope><scope>C1K</scope><scope>F28</scope><scope>FR3</scope><scope>H8D</scope><scope>H8G</scope><scope>H94</scope><scope>JG9</scope><scope>JQ2</scope><scope>K9.</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M7N</scope><scope>P64</scope><scope>RC3</scope><scope>7X8</scope></search><sort><creationdate>20190830</creationdate><title>AI surpasses humans at six-player poker</title><author>Blair, Alan ; Saffidine, Abdallah</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c413t-17233ab65a07836a28f4c6cc3589e285f4850067ab8932f812d74a4d69a421703</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Algorithms</topic><topic>Artificial intelligence</topic><topic>Card games</topic><topic>Checkers</topic><topic>Chess</topic><topic>Human performance</topic><topic>PERSPECTIVES</topic><topic>Randomness</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Blair, Alan</creatorcontrib><creatorcontrib>Saffidine, Abdallah</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>Aluminium Industry Abstracts</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Ceramic Abstracts</collection><collection>Chemoreception Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Ecology Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Materials Business File</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Copper Technical Reference Library</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Science (American Association for the Advancement of Science)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Blair, Alan</au><au>Saffidine, Abdallah</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>AI surpasses humans at six-player poker</atitle><jtitle>Science (American Association for the Advancement of Science)</jtitle><addtitle>Science</addtitle><date>2019-08-30</date><risdate>2019</risdate><volume>365</volume><issue>6456</issue><spage>864</spage><epage>865</epage><pages>864-865</pages><issn>0036-8075</issn><eissn>1095-9203</eissn><abstract>Self-learning Pluribus beats five humans in Texas hold'em showdown
Superhuman performance by artificial intelligence (AI) has been demonstrated in two-player, deterministic, zero-sum, perfect-information games (
1
) such as chess, checkers (
2
), Hex, and Go (
3
). Research using AI has broadened to include games with challenging attributes such as randomness, multiple players, or imperfect information. Randomness is a feature of dice games, and card games include the additional complexity that each player sees some cards that are hidden from others. These aspects more closely resemble real-world situations, and this research may thus lead to algorithms with wider applicability. On page 885 of this issue, Brown and Sandholm (
4
) show that a new computer player called Pluribus exceeds human performance for six-player Texas hold'em poker.</abstract><cop>United States</cop><pub>American Association for the Advancement of Science</pub><pmid>31467208</pmid><doi>10.1126/science.aay7774</doi><tpages>2</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0036-8075 |
| ispartof | Science (American Association for the Advancement of Science), 2019-08, Vol.365 (6456), p.864-865 |
| issn | 0036-8075 1095-9203 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_2283109982 |
| source | American Association for the Advancement of Science |
| subjects | Algorithms Artificial intelligence Card games Checkers Chess Human performance PERSPECTIVES Randomness |
| title | AI surpasses humans at six-player poker |
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