{"id":"https://openalex.org/W2589545309","doi":"https://doi.org/10.1109/cig.2016.7860387","title":"Deep Q-learning using redundant outputs in visual doom","display_name":"Deep Q-learning using redundant outputs in visual doom","publication_year":2016,"publication_date":"2016-09-01","ids":{"openalex":"https://openalex.org/W2589545309","doi":"https://doi.org/10.1109/cig.2016.7860387","mag":"2589545309"},"language":"en","primary_location":{"id":"doi:10.1109/cig.2016.7860387","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cig.2016.7860387","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE Conference on Computational Intelligence and Games (CIG)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018503719","display_name":"Hyunsoo Park","orcid":"https://orcid.org/0000-0001-6924-1919"},"institutions":[{"id":"https://openalex.org/I28777354","display_name":"Sejong University","ror":"https://ror.org/00aft1q37","country_code":"KR","type":"education","lineage":["https://openalex.org/I28777354"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyunsoo Park","raw_affiliation_strings":["Department of Computer Science and Engineering, Sejong University, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Sejong University, Seoul, South Korea","institution_ids":["https://openalex.org/I28777354"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076055880","display_name":"Kyung-Joong Kim","orcid":"https://orcid.org/0000-0002-7732-0817"},"institutions":[{"id":"https://openalex.org/I28777354","display_name":"Sejong University","ror":"https://ror.org/00aft1q37","country_code":"KR","type":"education","lineage":["https://openalex.org/I28777354"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Kyung-Joong Kim","raw_affiliation_strings":["Department of Computer Science and Engineering, Sejong University, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Sejong University, Seoul, South Korea","institution_ids":["https://openalex.org/I28777354"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I28777354"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"2"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9998000264167786,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9998000264167786,"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/T11574","display_name":"Artificial Intelligence in Games","score":0.9968000054359436,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9782999753952026,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.8926341533660889},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.787900447845459},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7386858463287354},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6723074913024902},{"id":"https://openalex.org/keywords/greedy-algorithm","display_name":"Greedy algorithm","score":0.5129567980766296},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5129351615905762},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5019321441650391},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.44393986463546753},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.0994907021522522},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07309257984161377}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8926341533660889},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.787900447845459},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7386858463287354},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6723074913024902},{"id":"https://openalex.org/C51823790","wikidata":"https://www.wikidata.org/wiki/Q504353","display_name":"Greedy algorithm","level":2,"score":0.5129567980766296},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5129351615905762},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5019321441650391},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.44393986463546753},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.0994907021522522},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07309257984161377},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cig.2016.7860387","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cig.2016.7860387","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE Conference on Computational Intelligence and Games (CIG)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1757796397","https://openalex.org/W2280163991","https://openalex.org/W2362143032","https://openalex.org/W2963871073","https://openalex.org/W3037207827","https://openalex.org/W4298857966","https://openalex.org/W6637967152","https://openalex.org/W6695011786","https://openalex.org/W6780559895"],"related_works":["https://openalex.org/W4387497383","https://openalex.org/W3183948672","https://openalex.org/W3173606202","https://openalex.org/W3110381201","https://openalex.org/W2948807893","https://openalex.org/W2935909890","https://openalex.org/W2778153218","https://openalex.org/W2758277628","https://openalex.org/W1531601525","https://openalex.org/W4306904969"],"abstract_inverted_index":{"Recently,":[0],"there":[1],"is":[2,19,72],"a":[3],"growing":[4],"interest":[5],"in":[6,10,23,36,42,53,68],"applying":[7],"deep":[8,16,43,75],"learning":[9,18,77],"game":[11,24],"AI":[12,25,57],"domain.":[13],"Among":[14],"them,":[15],"reinforcement":[17,44,76],"the":[20,69],"most":[21],"famous":[22],"communities.":[26],"In":[27],"this":[28],"paper,":[29],"we":[30],"propose":[31],"to":[32,38,89],"use":[33],"redundant":[34],"outputs":[35],"order":[37],"adapt":[39],"training":[40],"progress":[41],"learning.":[45],"We":[46],"compare":[47],"our":[48,83],"method":[49,85],"with":[50],"general":[51],"\u03b5-greedy":[52,90],"ViZDoom":[54],"platform.":[55],"Since":[56],"player":[58],"should":[59],"select":[60],"an":[61],"action":[62],"only":[63],"based":[64],"on":[65],"visual":[66],"input":[67],"platform,":[70],"it":[71],"suitable":[73],"for":[74],"research.":[78],"Experimental":[79],"results":[80],"show":[81],"that":[82],"proposed":[84],"archives":[86],"competitive":[87],"performance":[88],"without":[91],"parameter":[92],"tuning.":[93]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}