{"id":"https://openalex.org/W4206689471","doi":"https://doi.org/10.1109/cog52621.2021.9619147","title":"Heuristic Sampling for Fast Plausible Playouts","display_name":"Heuristic Sampling for Fast Plausible Playouts","publication_year":2021,"publication_date":"2021-08-17","ids":{"openalex":"https://openalex.org/W4206689471","doi":"https://doi.org/10.1109/cog52621.2021.9619147"},"language":"en","primary_location":{"id":"doi:10.1109/cog52621.2021.9619147","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cog52621.2021.9619147","pdf_url":null,"source":{"id":"https://openalex.org/S4363608335","display_name":"2021 IEEE Conference on Games (CoG)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Conference on Games (CoG)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://cris.maastrichtuniversity.nl/en/publications/125f8adf-e323-4d0f-aa36-893ae390d35a","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065924402","display_name":"Cameron Browne","orcid":"https://orcid.org/0000-0003-2997-3255"},"institutions":[{"id":"https://openalex.org/I34352273","display_name":"Maastricht University","ror":"https://ror.org/02jz4aj89","country_code":"NL","type":"education","lineage":["https://openalex.org/I34352273"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Cameron Browne","raw_affiliation_strings":["Department of Data Science and Knowledge Engineering, Maastricht University, Maastricht, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Department of Data Science and Knowledge Engineering, Maastricht University, Maastricht, The Netherlands","institution_ids":["https://openalex.org/I34352273"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111669977","display_name":"Fabio Barbero","orcid":null},"institutions":[{"id":"https://openalex.org/I34352273","display_name":"Maastricht University","ror":"https://ror.org/02jz4aj89","country_code":"NL","type":"education","lineage":["https://openalex.org/I34352273"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Fabio Barbero","raw_affiliation_strings":["Department of Data Science and Knowledge Engineering, Maastricht University, Maastricht, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Department of Data Science and Knowledge Engineering, Maastricht University, Maastricht, The Netherlands","institution_ids":["https://openalex.org/I34352273"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5065924402"],"corresponding_institution_ids":["https://openalex.org/I34352273"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20517854,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11574","display_name":"Artificial Intelligence in Games","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11574","display_name":"Artificial Intelligence in Games","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11674","display_name":"Sports Analytics and Performance","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.984499990940094,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.7953026294708252},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.7287509441375732},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.709086000919342},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.510625422000885},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44477319717407227},{"id":"https://openalex.org/keywords/evaluation-function","display_name":"Evaluation function","score":0.441109836101532},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.4129326045513153},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.35809916257858276},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3266916871070862},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.32500630617141724},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2035168707370758},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.07091552019119263}],"concepts":[{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.7953026294708252},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.7287509441375732},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.709086000919342},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.510625422000885},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44477319717407227},{"id":"https://openalex.org/C131806220","wikidata":"https://www.wikidata.org/wiki/Q852705","display_name":"Evaluation function","level":2,"score":0.441109836101532},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.4129326045513153},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.35809916257858276},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3266916871070862},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32500630617141724},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2035168707370758},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.07091552019119263},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/cog52621.2021.9619147","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cog52621.2021.9619147","pdf_url":null,"source":{"id":"https://openalex.org/S4363608335","display_name":"2021 IEEE Conference on Games (CoG)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Conference on Games (CoG)","raw_type":"proceedings-article"},{"id":"pmh:oai:cris.maastrichtuniversity.nl:openaire/125f8adf-e323-4d0f-aa36-893ae390d35a","is_oa":true,"landing_page_url":"https://cris.maastrichtuniversity.nl/en/publications/125f8adf-e323-4d0f-aa36-893ae390d35a","pdf_url":null,"source":{"id":"https://openalex.org/S4306402616","display_name":"Research Publications (Maastricht University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I34352273","host_organization_name":"Maastricht University","host_organization_lineage":["https://openalex.org/I34352273"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Browne, C & Barbero, F 2021, Heuristic Sampling for Fast Plausible Playouts. in 2021 IEEE CONFERENCE ON GAMES (COG). IEEE, IEEE Conference on Computational Intelligence and Games, pp. 1042-1045, IEEE Conference on Games (IEEE CoG), Copenhagen, Denmark, 17/08/21. https://doi.org/10.1109/COG52621.2021.9619147","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":{"id":"pmh:oai:cris.maastrichtuniversity.nl:openaire/125f8adf-e323-4d0f-aa36-893ae390d35a","is_oa":true,"landing_page_url":"https://cris.maastrichtuniversity.nl/en/publications/125f8adf-e323-4d0f-aa36-893ae390d35a","pdf_url":null,"source":{"id":"https://openalex.org/S4306402616","display_name":"Research Publications (Maastricht University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I34352273","host_organization_name":"Maastricht University","host_organization_lineage":["https://openalex.org/I34352273"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Browne, C & Barbero, F 2021, Heuristic Sampling for Fast Plausible Playouts. in 2021 IEEE CONFERENCE ON GAMES (COG). IEEE, IEEE Conference on Computational Intelligence and Games, pp. 1042-1045, IEEE Conference on Games (IEEE CoG), Copenhagen, Denmark, 17/08/21. https://doi.org/10.1109/COG52621.2021.9619147","raw_type":"info:eu-repo/semantics/publishedVersion"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5117483468","display_name":null,"funder_award_id":"771292","funder_id":"https://openalex.org/F4320334678","funder_display_name":"European Research Council"}],"funders":[{"id":"https://openalex.org/F4320334678","display_name":"European Research Council","ror":"https://ror.org/0472cxd90"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1598714892","https://openalex.org/W1968887996","https://openalex.org/W2013189618","https://openalex.org/W2296076706","https://openalex.org/W2896888044","https://openalex.org/W2943930939","https://openalex.org/W6635924140","https://openalex.org/W6762220698"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4224009465","https://openalex.org/W4306674287","https://openalex.org/W2560759630","https://openalex.org/W126812865","https://openalex.org/W2182517271","https://openalex.org/W2538664931","https://openalex.org/W2349967715","https://openalex.org/W44209425","https://openalex.org/W2358915062"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"Heuristic":[3],"Sampling":[4],"(HS)":[5],"for":[6,10],"generating":[7],"self-play":[8],"trials":[9],"games":[11],"with":[12,18],"a":[13],"defined":[14],"state":[15],"evaluation":[16],"function,":[17],"speeds":[19],"comparable":[20,28],"to":[21,29,41],"random":[22],"playouts":[23],"but":[24],"game":[25],"length":[26],"estimates":[27],"those":[30],"produced":[31],"by":[32],"intelligent":[33],"AI":[34],"agents.":[35],"HS":[36],"produces":[37],"plausible":[38],"results":[39],"up":[40],"thousands":[42],"of":[43],"times":[44],"faster":[45],"than":[46],"more":[47],"rigorous":[48],"methods.":[49]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}