{"id":"https://openalex.org/W4409427770","doi":"https://doi.org/10.1109/giest62955.2024.10960023","title":"Developing Game AI for Classic Games Using Reinforcement Learning","display_name":"Developing Game AI for Classic Games Using Reinforcement Learning","publication_year":2024,"publication_date":"2024-10-25","ids":{"openalex":"https://openalex.org/W4409427770","doi":"https://doi.org/10.1109/giest62955.2024.10960023"},"language":"en","primary_location":{"id":"doi:10.1109/giest62955.2024.10960023","doi":"https://doi.org/10.1109/giest62955.2024.10960023","is_oa":false,"landing_page_url":"https://doi.org/10.1109/giest62955.2024.10960023","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 1st International Conference on Green Industrial Electronics and Sustainable Technologies (GIEST)","raw_type":"proceedings-article"},"volume":null,"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/A5049828648","display_name":"Shivam Gupta","orcid":"https://orcid.org/0000-0003-0633-3917","observed_orcids":["https://orcid.org/0000-0003-0633-3917"]},"institutions":[{"id":"https://openalex.org/I101407740","display_name":"Chandigarh University","ror":"https://ror.org/05t4pvx35","country_code":"IN","type":"education","lineage":["https://openalex.org/I101407740"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Shivam Gupta","raw_affiliation_strings":["Chandigarh University,Apex Institute of Technology (CSE),Mohali,Punjab,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chandigarh University,Apex Institute of Technology (CSE),Mohali,Punjab,India","institution_ids":["https://openalex.org/I101407740"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006107324","display_name":"Nancy Nancy","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I101407740","display_name":"Chandigarh University","ror":"https://ror.org/05t4pvx35","country_code":"IN","type":"education","lineage":["https://openalex.org/I101407740"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Nancy Nancy","raw_affiliation_strings":["Chandigarh University,Apex Institute of Technology (CSE),Mohali,Punjab,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chandigarh University,Apex Institute of Technology (CSE),Mohali,Punjab,India","institution_ids":["https://openalex.org/I101407740"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5092191984","display_name":"Priyanshu Kumar Saw","orcid":"https://orcid.org/0009-0002-3535-766X","observed_orcids":["https://orcid.org/0009-0002-3535-766X"]},"institutions":[{"id":"https://openalex.org/I101407740","display_name":"Chandigarh University","ror":"https://ror.org/05t4pvx35","country_code":"IN","type":"education","lineage":["https://openalex.org/I101407740"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Priyanshu Kumar Saw","raw_affiliation_strings":["Chandigarh University,Apex Institute of Technology (CSE),Mohali,Punjab,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chandigarh University,Apex Institute of Technology (CSE),Mohali,Punjab,India","institution_ids":["https://openalex.org/I101407740"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100760310","display_name":"Atul Raj","orcid":"https://orcid.org/0000-0001-8409-7468","observed_orcids":["https://orcid.org/0000-0001-8409-7468"]},"institutions":[{"id":"https://openalex.org/I101407740","display_name":"Chandigarh University","ror":"https://ror.org/05t4pvx35","country_code":"IN","type":"education","lineage":["https://openalex.org/I101407740"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Atul Raj","raw_affiliation_strings":["Chandigarh University,Apex Institute of Technology (CSE),Mohali,Punjab,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chandigarh University,Apex Institute of Technology (CSE),Mohali,Punjab,India","institution_ids":["https://openalex.org/I101407740"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113097108","display_name":"Amit Kumar","orcid":"https://orcid.org/0009-0002-6463-235X","observed_orcids":["https://orcid.org/0009-0002-6463-235X"]},"institutions":[{"id":"https://openalex.org/I101407740","display_name":"Chandigarh University","ror":"https://ror.org/05t4pvx35","country_code":"IN","type":"education","lineage":["https://openalex.org/I101407740"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Amit Kumar","raw_affiliation_strings":["Chandigarh University,Apex Institute of Technology (CSE),Mohali,Punjab,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chandigarh University,Apex Institute of Technology (CSE),Mohali,Punjab,India","institution_ids":["https://openalex.org/I101407740"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102899465","display_name":"Kushagra Agrawal","orcid":"https://orcid.org/0009-0006-7753-175X","observed_orcids":["https://orcid.org/0009-0006-7753-175X"]},"institutions":[{"id":"https://openalex.org/I101407740","display_name":"Chandigarh University","ror":"https://ror.org/05t4pvx35","country_code":"IN","type":"education","lineage":["https://openalex.org/I101407740"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Kushagra Agrawal","raw_affiliation_strings":["Chandigarh University,Apex Institute of Technology (CSE),Mohali,Punjab,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chandigarh University,Apex Institute of Technology (CSE),Mohali,Punjab,India","institution_ids":["https://openalex.org/I101407740"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I101407740"],"apc_list":null,"apc_paid":null,"fwci":0.2937,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.57628972,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.6830999851226807,"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":0.6830999851226807,"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":0.3158999979496002,"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/T13904","display_name":"Artificial Intelligence Applications","score":0.00039999998989515007,"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/game-ai","display_name":"game AI","score":0.9879999756813049},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"reinforcement learning","score":0.6940000057220459},{"id":"https://openalex.org/keywords/snake-game","display_name":"snake game","score":0.8040000200271606},{"id":"https://openalex.org/keywords/mario","display_name":"Mario","score":0.5979999899864197},{"id":"https://openalex.org/keywords/q-learning","display_name":"Q-learning","score":0.9929999709129333},{"id":"https://openalex.org/keywords/proximal-policy-optimization","display_name":"proximal policy optimization","score":0.9229999780654907},{"id":"https://openalex.org/keywords/continuous-action-spaces","display_name":"continuous action spaces","score":0.9129999876022339},{"id":"https://openalex.org/keywords/discrete-action-space","display_name":"discrete action space","score":0.859000027179718},{"id":"https://openalex.org/keywords/game-agents","display_name":"game-playing agents","score":0.5669999718666077},{"id":"https://openalex.org/keywords/classic-video-games","display_name":"classic video games","score":0.4740000069141388}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7084722518920898},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6640766859054565},{"id":"https://openalex.org/C47187476","wikidata":"https://www.wikidata.org/wiki/Q12336660","display_name":"Video game design","level":3,"score":0.49695685505867004},{"id":"https://openalex.org/C170828538","wikidata":"https://www.wikidata.org/wiki/Q1751513","display_name":"Game mechanics","level":2,"score":0.4170326590538025},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41623392701148987},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.36359813809394836},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.34673765301704407}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/giest62955.2024.10960023","doi":"https://doi.org/10.1109/giest62955.2024.10960023","is_oa":false,"landing_page_url":"https://doi.org/10.1109/giest62955.2024.10960023","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 1st International Conference on Green Industrial Electronics and Sustainable Technologies (GIEST)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"sustainable_development_goals_aurora":[{"display_name":"Partnerships for the goals","score":0.44999998807907104,"id":"https://metadata.un.org/sdg/17"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W3186392522","https://openalex.org/W4224879017","https://openalex.org/W4289641564","https://openalex.org/W4294753973","https://openalex.org/W4295357681","https://openalex.org/W4309742989","https://openalex.org/W4322751609","https://openalex.org/W4376116607","https://openalex.org/W4385236624","https://openalex.org/W4385893198","https://openalex.org/W4389302446","https://openalex.org/W4391054859","https://openalex.org/W4391182759","https://openalex.org/W4391528906","https://openalex.org/W4392155943","https://openalex.org/W4393267622","https://openalex.org/W4393268839","https://openalex.org/W4398226217","https://openalex.org/W4399602118","https://openalex.org/W4400764196"],"related_works":["https://openalex.org/W4294947912","https://openalex.org/W4231050501","https://openalex.org/W2974032926","https://openalex.org/W4288103881","https://openalex.org/W4311459595","https://openalex.org/W2086822623","https://openalex.org/W2972448646","https://openalex.org/W1583852935","https://openalex.org/W571219209","https://openalex.org/W4381199393"],"abstract_inverted_index":{"New":[0],"accomplishments":[1],"have":[2],"contributed":[3],"widely":[4],"to":[5,11,29,52,71,100],"game":[6,15,69,227],"development":[7],"especially":[8],"with":[9,37,155],"respect":[10],"production":[12],"of":[13,19,144,149,173,193,196,216,226],"intelligent":[14],"playing":[16],"entities.":[17],"Most":[18],"the":[20,67,73,102,118,145,156,168,179,183,191,194,209,214],"archetypal":[21],"approaches":[22,204],"for":[23,56,112],"designing":[24],"AI":[25,54,211],"in":[26,32,66,80,153,213],"games":[27],"fail":[28],"work":[30],"properly":[31],"complex":[33],"and":[34,61,130,160,171,182,198,200,219],"real-time":[35],"environments":[36,154,218],"huge":[38],"action":[39,75,133],"space.":[40,84,134],"This":[41,165,188],"research":[42],"addresses":[43],"these":[44,174,203],"challenges":[45],"by":[46,105],"utilizing":[47],"reinforcement":[48,150],"learning":[49,106,151],"(RL)":[50],"techniques":[51],"design":[53],"models":[55],"two":[57],"well-known":[58],"games:":[59],"Snake":[60,68],"Mario.":[62],"The":[63,110],"main":[64],"challenge":[65],"is":[70,121],"find":[72],"best":[74],"within":[76],"a":[77,81,125,131],"given":[78],"state":[79],"discrete":[82],"state-action":[83],"To":[85],"solve":[86],"this,":[87,136],"we":[88,137],"apply":[89],"Q-learning,":[90],"an":[91],"uncomplicated,":[92],"but":[93],"highly":[94],"effective":[95,147,207],"RL":[96],"algorithm":[97],"that":[98,122],"aims":[99],"accumulate":[101],"maximum":[103],"reward":[104],"from":[107],"previous":[108],"experiences.":[109],"reason":[111],"Mario":[113,123],"being":[114],"more":[115,206],"challenging":[116],"than":[117,208],"other":[119],"one":[120,143],"has":[124],"high":[126],"dimensional":[127],"input":[128],"space":[129,159],"continuous":[132,157],"For":[135],"use":[138],"Proximal":[139],"Policy":[140],"Optimization":[141],"(PPO),":[142],"most":[146],"methods":[148],"applicable":[152],"decision":[158],"stochastic":[161],"nonlinear":[162],"differential":[163],"equations.":[164],"paper":[166],"describes":[167],"design,":[169],"deployment,":[170],"evaluation":[172],"Reinforcement":[175],"Learning":[176],"agents":[177],"where":[178],"major":[180],"difficulties":[181],"rectified":[184],"methodologies":[185],"are":[186,205],"described.":[187],"study":[189],"compares":[190],"efficiency":[192],"application":[195],"Q-learning":[197],"PPO":[199],"shows":[201],"how":[202],"classical":[210],"technologies":[212],"context":[215],"gaming":[217],"bring":[220],"valuable":[221],"contributions":[222],"toward":[223],"further":[224],"enhancement":[225],"AI.":[228]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2025-10-10T00:00:00"}
