{"id":"https://openalex.org/W4393161688","doi":"https://doi.org/10.1609/aaai.v38i21.30565","title":"MANDREL: Modular Reinforcement Learning Pipelines for Material Discovery","display_name":"MANDREL: Modular Reinforcement Learning Pipelines for Material Discovery","publication_year":2024,"publication_date":"2024-03-24","ids":{"openalex":"https://openalex.org/W4393161688","doi":"https://doi.org/10.1609/aaai.v38i21.30565"},"language":"en","primary_location":{"id":"doi:10.1609/aaai.v38i21.30565","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1609/aaai.v38i21.30565","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/30565/32727","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/30565/32727","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5094241488","display_name":"Clyde Fare","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Clyde Fare","raw_affiliation_strings":["IBM Research Europe"],"affiliations":[{"raw_affiliation_string":"IBM Research Europe","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041831295","display_name":"George K. Holt","orcid":"https://orcid.org/0000-0001-6814-9117"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"George K. Holt","raw_affiliation_strings":["STFC Hartree"],"affiliations":[{"raw_affiliation_string":"STFC Hartree","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070226727","display_name":"Lamogha Chiazor","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lamogha Chiazor","raw_affiliation_strings":["IBM Research Europe"],"affiliations":[{"raw_affiliation_string":"IBM Research Europe","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061522183","display_name":"Michail Smyrnakis","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Michail Smyrnakis","raw_affiliation_strings":["STFC Hartree"],"affiliations":[{"raw_affiliation_string":"STFC Hartree","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013733781","display_name":"Robert W. Tracey","orcid":"https://orcid.org/0000-0002-9947-2256"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Robert Tracey","raw_affiliation_strings":["IBM Research Europe"],"affiliations":[{"raw_affiliation_string":"IBM Research Europe","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038742043","display_name":"Lan Thu Hoang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lan Hoang","raw_affiliation_strings":["IBM Research Europe"],"affiliations":[{"raw_affiliation_string":"IBM Research Europe","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5094241488"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09900166,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"38","issue":"21","first_page":"23787","last_page":"23789"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12282","display_name":"Mineral Processing and Grinding","score":0.944599986076355,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12282","display_name":"Mineral Processing and Grinding","score":0.944599986076355,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/mandrel","display_name":"Mandrel","score":0.7686207294464111},{"id":"https://openalex.org/keywords/modular-design","display_name":"Modular design","score":0.7356804013252258},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6829918026924133},{"id":"https://openalex.org/keywords/reinforcement","display_name":"Reinforcement","score":0.561651349067688},{"id":"https://openalex.org/keywords/pipeline-transport","display_name":"Pipeline transport","score":0.5206927061080933},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.42777228355407715},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.3698267936706543},{"id":"https://openalex.org/keywords/structural-engineering","display_name":"Structural engineering","score":0.3176690936088562},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2981879413127899},{"id":"https://openalex.org/keywords/mechanical-engineering","display_name":"Mechanical engineering","score":0.2742987871170044},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.100995272397995}],"concepts":[{"id":"https://openalex.org/C2777918083","wikidata":"https://www.wikidata.org/wiki/Q136706","display_name":"Mandrel","level":2,"score":0.7686207294464111},{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.7356804013252258},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6829918026924133},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.561651349067688},{"id":"https://openalex.org/C175309249","wikidata":"https://www.wikidata.org/wiki/Q725864","display_name":"Pipeline transport","level":2,"score":0.5206927061080933},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.42777228355407715},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3698267936706543},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.3176690936088562},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2981879413127899},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.2742987871170044},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.100995272397995}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v38i21.30565","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1609/aaai.v38i21.30565","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/30565/32727","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v38i21.30565","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1609/aaai.v38i21.30565","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/30565/32727","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320334632","display_name":"Science and Technology Facilities Council","ror":"https://ror.org/057g20z61"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4393161688.pdf","grobid_xml":"https://content.openalex.org/works/W4393161688.grobid-xml"},"referenced_works_count":17,"referenced_works":["https://openalex.org/W1975147762","https://openalex.org/W2034549041","https://openalex.org/W2044834685","https://openalex.org/W2618625858","https://openalex.org/W2977044154","https://openalex.org/W3005864172","https://openalex.org/W3014154196","https://openalex.org/W3104956673","https://openalex.org/W3158331815","https://openalex.org/W4205447329","https://openalex.org/W4211049957","https://openalex.org/W4226197958","https://openalex.org/W4243270491","https://openalex.org/W4306179830","https://openalex.org/W4361192921","https://openalex.org/W6642553800","https://openalex.org/W6658997944"],"related_works":["https://openalex.org/W2361944878","https://openalex.org/W2501227584","https://openalex.org/W2073724610","https://openalex.org/W2391903891","https://openalex.org/W2144387523","https://openalex.org/W3134432553","https://openalex.org/W2386673474","https://openalex.org/W2312959737","https://openalex.org/W2768345513","https://openalex.org/W2067882923"],"abstract_inverted_index":{"AI-driven":[0],"materials":[1],"discovery":[2],"is":[3],"evolving":[4],"rapidly":[5],"with":[6],"new":[7],"approaches":[8],"and":[9,13,33,47,51,66,84],"pipelines":[10,17,46],"for":[11,30,55,96],"experimentation":[12,32],"design.":[14],"However,":[15],"the":[16,49,56,72,89],"are":[18],"often":[19],"designed":[20],"in":[21],"isolation.":[22],"We":[23],"introduce":[24],"a":[25],"modular":[26],"reinforcement":[27,43],"learning":[28,44],"framework":[29,41],"inter-operable":[31],"design":[34,90],"of":[35,53,82,91],"tailored,":[36],"novel":[37,92],"molecular":[38,61,64],"species.":[39],"The":[40],"unifies":[42],"(RL)":[45],"allows":[48],"mixing":[50],"matching":[52],"choices":[54],"underlying":[57],"chemical":[58],"action":[59],"space,":[60],"representation,":[62],"desired":[63],"properties,":[65],"RL":[67],"algorithm.":[68],"Our":[69],"demo":[70],"showcases":[71],"framework's":[73],"capabilities":[74],"applied":[75],"to":[76],"benchmark":[77],"problems":[78],"like":[79],"quantitative":[80],"estimate":[81],"drug-likeness":[83],"PLogP,":[85],"as":[86,88],"well":[87],"small":[93],"molecule":[94],"solvents":[95],"carbon":[97],"capture.":[98]},"counts_by_year":[],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2025-10-10T00:00:00"}
