{"id":"https://openalex.org/W2975704836","doi":"https://doi.org/10.1109/cig.2019.8847950","title":"Visualization of Deep Reinforcement Learning using Grad-CAM: How AI Plays Atari Games?","display_name":"Visualization of Deep Reinforcement Learning using Grad-CAM: How AI Plays Atari Games?","publication_year":2019,"publication_date":"2019-08-01","ids":{"openalex":"https://openalex.org/W2975704836","doi":"https://doi.org/10.1109/cig.2019.8847950","mag":"2975704836"},"language":"en","primary_location":{"id":"doi:10.1109/cig.2019.8847950","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cig.2019.8847950","pdf_url":null,"source":{"id":"https://openalex.org/S4306498491","display_name":"2019 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":"2019 IEEE Conference on Games (CoG)","raw_type":"proceedings-article"},"type":"article","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/A5028014790","display_name":"Ho-Taek Joo","orcid":"https://orcid.org/0000-0002-2286-3216"},"institutions":[{"id":"https://openalex.org/I39534123","display_name":"Gwangju Institute of Science and Technology","ror":"https://ror.org/024kbgz78","country_code":"KR","type":"education","lineage":["https://openalex.org/I39534123"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Ho-Taek Joo","raw_affiliation_strings":["Institute of Integrated Technology GIST, Gwangju, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Integrated Technology GIST, Gwangju, South Korea","institution_ids":["https://openalex.org/I39534123"]}]},{"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/I39534123","display_name":"Gwangju Institute of Science and Technology","ror":"https://ror.org/024kbgz78","country_code":"KR","type":"education","lineage":["https://openalex.org/I39534123"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Kyung-Joong Kim","raw_affiliation_strings":["Institute of Integrated Technology GIST, Gwangju, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Integrated Technology GIST, Gwangju, South Korea","institution_ids":["https://openalex.org/I39534123"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I39534123"],"apc_list":null,"apc_paid":null,"fwci":2.3901,"has_fulltext":false,"cited_by_count":49,"citation_normalized_percentile":{"value":0.9113817,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9997000098228455,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9997000098228455,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9980000257492065,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.991599977016449,"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/computer-science","display_name":"Computer science","score":0.8186007738113403},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7919381856918335},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.7316504716873169},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6899129152297974},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.6838383674621582},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5968976616859436},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.3654208779335022},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32122936844825745}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8186007738113403},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7919381856918335},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.7316504716873169},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6899129152297974},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.6838383674621582},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5968976616859436},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3654208779335022},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32122936844825745},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cig.2019.8847950","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cig.2019.8847950","pdf_url":null,"source":{"id":"https://openalex.org/S4306498491","display_name":"2019 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":"2019 IEEE Conference on Games (CoG)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8299999833106995,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W1849277567","https://openalex.org/W2145339207","https://openalex.org/W2962858109","https://openalex.org/W2964043796","https://openalex.org/W4226065182","https://openalex.org/W4389510386","https://openalex.org/W6692846177"],"related_works":["https://openalex.org/W2068608913","https://openalex.org/W4306904969","https://openalex.org/W2138720691","https://openalex.org/W4362501864","https://openalex.org/W4380318855","https://openalex.org/W3084456289","https://openalex.org/W3124914020","https://openalex.org/W2024136090","https://openalex.org/W4391331176","https://openalex.org/W2031695474"],"abstract_inverted_index":{"Deep":[0],"Reinforcement":[1],"Learning":[2],"(DRL)":[3],"allows":[4],"agents":[5],"to":[6,9,17,33,36,93],"learn":[7],"strategies":[8],"solve":[10,18],"complex":[11],"tasks.":[12],"It":[13],"has":[14,66],"been":[15,67],"applied":[16],"various":[19],"problems":[20,39],"such":[21],"as":[22],"natural":[23],"language":[24],"processing,":[25],"games,":[26],"etc.":[27],"However,":[28],"it":[29],"is":[30,43,122],"still":[31],"difficult":[32],"apply":[34],"DRL":[35],"certain":[37],"real-world":[38],"because":[40],"each":[41],"action":[42],"not":[44],"predictable,":[45],"and":[46],"we":[47,91,102],"cannot":[48],"know":[49],"why":[50],"the":[51,77,84,98,104,119],"results":[52,85,114],"are":[53],"coming":[54],"out.":[55],"For":[56],"this":[57,71,89],"reason,":[58],"a":[59,74],"technology":[60,72],"called":[61],"eXplainable":[62],"Artificial":[63],"Intelligence":[64],"(XAI)":[65],"recently":[68],"developed.":[69],"As":[70],"shows":[73],"visualization":[75],"of":[76,86,97,106,118],"AI":[78,107],"process,":[79],"people":[80],"can":[81],"easily":[82],"understand":[83],"AI.":[87],"In":[88],"paper,":[90],"proposed":[92],"use":[94],"Grad-CAM,":[95],"one":[96,126],"XAI":[99],"techniques,":[100],"when":[101,125],"visualize":[103],"behaviors":[105],"players":[108],"trained":[109],"by":[110],"DRL.":[111],"Our":[112],"experimental":[113],"show":[115],"which":[116],"part":[117],"input":[120],"state":[121],"focused":[123],"on":[124],"well-trained":[127],"agent":[128],"takes":[129],"action.":[130]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-04T07:58:01.006859","created_date":"2025-10-10T00:00:00"}
