{"id":"https://openalex.org/W4413321290","doi":"https://doi.org/10.1109/cog64752.2025.11114131","title":"NTRL: Encounter Generation via Reinforcement Learning for Dynamic Difficulty Adjustment in Dungeons and Dragons","display_name":"NTRL: Encounter Generation via Reinforcement Learning for Dynamic Difficulty Adjustment in Dungeons and Dragons","publication_year":2025,"publication_date":"2025-08-19","ids":{"openalex":"https://openalex.org/W4413321290","doi":"https://doi.org/10.1109/cog64752.2025.11114131"},"language":"en","primary_location":{"id":"doi:10.1109/cog64752.2025.11114131","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cog64752.2025.11114131","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE Conference on Games (CoG)","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/A5011709924","display_name":"Carlo Romeo","orcid":"https://orcid.org/0000-0002-7287-0019"},"institutions":[{"id":"https://openalex.org/I45084792","display_name":"University of Florence","ror":"https://ror.org/04jr1s763","country_code":"IT","type":"education","lineage":["https://openalex.org/I45084792"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Carlo Romeo","raw_affiliation_strings":["University of Florence"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Florence","institution_ids":["https://openalex.org/I45084792"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064029620","display_name":"Andrew D. Bagdanov","orcid":"https://orcid.org/0000-0001-6408-7043"},"institutions":[{"id":"https://openalex.org/I45084792","display_name":"University of Florence","ror":"https://ror.org/04jr1s763","country_code":"IT","type":"education","lineage":["https://openalex.org/I45084792"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Andrew D. Bagdanov","raw_affiliation_strings":["University of Florence"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Florence","institution_ids":["https://openalex.org/I45084792"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I45084792"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11574","display_name":"Artificial Intelligence in Games","score":0.9840999841690063,"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":0.9840999841690063,"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/T11197","display_name":"Digital Games and Media","score":0.9424999952316284,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social 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":0.7757226228713989},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6955161690711975},{"id":"https://openalex.org/keywords/reinforcement","display_name":"Reinforcement","score":0.5219456553459167},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36888670921325684},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.32537296414375305},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.21992120146751404},{"id":"https://openalex.org/keywords/social-psychology","display_name":"Social psychology","score":0.10872423648834229}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7757226228713989},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6955161690711975},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.5219456553459167},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36888670921325684},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.32537296414375305},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.21992120146751404},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.10872423648834229}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/cog64752.2025.11114131","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cog64752.2025.11114131","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE Conference on Games (CoG)","raw_type":"proceedings-article"},{"id":"pmh:oai:flore.unifi.it:2158/1442918","is_oa":false,"landing_page_url":"https://hdl.handle.net/2158/1442918","pdf_url":null,"source":{"id":"https://openalex.org/S4306402033","display_name":"Florence Research (University of Florence)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45084792","host_organization_name":"University of Florence","host_organization_lineage":["https://openalex.org/I45084792"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W2112420033","https://openalex.org/W2126316555","https://openalex.org/W4241811150","https://openalex.org/W4313343220","https://openalex.org/W4391054831","https://openalex.org/W4392717068","https://openalex.org/W4395468672","https://openalex.org/W4402118506","https://openalex.org/W4404445390"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W4310083477","https://openalex.org/W2328553770","https://openalex.org/W2920061524","https://openalex.org/W1977959518","https://openalex.org/W2038908348","https://openalex.org/W2107890255","https://openalex.org/W2106552856"],"abstract_inverted_index":{"Balancing":[0],"combat":[1,58,90,133,175],"encounters":[2,71,87,148,159],"in":[3,55,141,156,179],"Dungeons":[4],"&":[5],"Dragons":[6],"(D&D)":[7],"is":[8,189],"a":[9,46,66,180],"complex":[10],"task":[11],"that":[12,49,182],"requires":[13],"Dungeon":[14,163],"Masters":[15],"(DM)":[16],"to":[17,88,101,136],"manually":[18],"assess":[19],"party":[20,75,102,127],"strength,":[21],"enemy":[22],"composition,":[23],"and":[24,116,139],"dynamic":[25],"player":[26,121],"interactions":[27],"while":[28,123,176],"avoiding":[29],"interruption":[30],"of":[31,120,132,174],"the":[32,63,118,146,171],"narrative":[33],"flow.":[34],"In":[35,78],"this":[36],"paper":[37],"we":[38],"propose":[39],"Encounter":[40],"Generation":[41],"via":[42,57],"Reinforcement":[43],"Learning":[44],"(NTRL),":[45],"novel":[47],"approach":[48],"automates":[50],"Dynamic":[51],"Difficulty":[52],"Adjustment":[53],"(DDA)":[54],"D&D":[56],"encounter":[59],"design.":[60],"By":[61],"framing":[62],"problem":[64],"as":[65],"contextual":[67],"bandit,":[68],"NTRL":[69,84,165],"generates":[70],"based":[72],"on":[73],"real-time":[74],"members":[76],"attributes.":[77],"comparison":[79,157],"with":[80,158],"classic":[81],"DM":[82],"heuristics,":[83],"iteratively":[85],"optimizes":[86],"extend":[89],"longevity":[91],"(<tex":[92,108],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[93,109],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$+\\mathbf{2":[94],"0":[95,96],"\\%}$</tex>),":[97,115],"increases":[98],"damage":[99],"dealt":[100],"members,":[103],"reducing":[104],"post-combat":[105],"hit":[106],"points":[107],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\mathbf{-":[110],"1":[111],"6.":[112],"6":[113],"7":[114],"raises":[117],"number":[119],"deaths":[122],"maintaining":[124],"low":[125],"total":[126],"kills":[128],"(TPK).":[129],"The":[130],"intensification":[131],"forces":[134],"players":[135],"act":[137],"wisely":[138],"engage":[140],"tactical":[142],"maneuvers,":[143],"even":[144],"though":[145],"generated":[147],"guarantee":[149],"high":[150],"win":[151],"rates":[152],"(70":[153],"%).":[154],"Even":[155],"designed":[160],"by":[161,169],"human":[162],"Masters,":[164],"demonstrates":[166],"superior":[167],"performance":[168],"enhancing":[170],"strategic":[172],"depth":[173],"increasing":[177],"difficulty":[178],"manner":[181],"preserves":[183],"overall":[184],"game":[185],"fairness.":[186],"Source":[187],"code":[188],"available":[190],"at":[191],"github.com/CarloRomeo427/NTRL.":[192]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}