{"id":"https://openalex.org/W7128511276","doi":"https://doi.org/10.48550/arxiv.2602.08616","title":"Breaking the Grid: Distance-Guided Reinforcement Learning in Large Discrete and Hybrid Action Spaces","display_name":"Breaking the Grid: Distance-Guided Reinforcement Learning in Large Discrete and Hybrid Action Spaces","publication_year":2026,"publication_date":"2026-02-09","ids":{"openalex":"https://openalex.org/W7128511276","doi":"https://doi.org/10.48550/arxiv.2602.08616"},"language":"en","primary_location":{"id":"pmh:doi:10.48550/arxiv.2602.08616","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101280423","display_name":"Heiko Hoppe","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Hoppe, Heiko","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032023486","display_name":"Fabian Akkerman","orcid":"https://orcid.org/0000-0001-8055-9864"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Akkerman, Fabian","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043700615","display_name":"Wouter van Heeswijk","orcid":"https://orcid.org/0000-0002-5413-9660"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"van Heeswijk, Wouter","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5034416720","display_name":"Maximilian Schiffer","orcid":"https://orcid.org/0000-0003-2682-4975"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Schiffer, Maximilian","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101280423"],"corresponding_institution_ids":[],"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.717199981212616,"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":0.717199981212616,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.049800001084804535,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.031099999323487282,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.7875999808311462},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.7723000049591064},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6854000091552734},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.5404999852180481},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.4968999922275543},{"id":"https://openalex.org/keywords/cardinality","display_name":"Cardinality (data modeling)","score":0.45170000195503235},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.4348999857902527},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.4271000027656555},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.36469998955726624}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7875999808311462},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.7723000049591064},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6854000091552734},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.646399974822998},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.5404999852180481},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.4968999922275543},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4595000147819519},{"id":"https://openalex.org/C87117476","wikidata":"https://www.wikidata.org/wiki/Q362383","display_name":"Cardinality (data modeling)","level":2,"score":0.45170000195503235},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4429999887943268},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.4348999857902527},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.4271000027656555},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.387800008058548},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.36970001459121704},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.36469998955726624},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.3440999984741211},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.34139999747276306},{"id":"https://openalex.org/C205606062","wikidata":"https://www.wikidata.org/wiki/Q5249645","display_name":"Decoupling (probability)","level":2,"score":0.33640000224113464},{"id":"https://openalex.org/C72169020","wikidata":"https://www.wikidata.org/wiki/Q194404","display_name":"Monotonic function","level":2,"score":0.33059999346733093},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.29249998927116394},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.2856000065803528},{"id":"https://openalex.org/C166109690","wikidata":"https://www.wikidata.org/wiki/Q4677422","display_name":"Action selection","level":3,"score":0.2743000090122223},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.27090001106262207},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.26899999380111694},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.26579999923706055},{"id":"https://openalex.org/C188116033","wikidata":"https://www.wikidata.org/wiki/Q2664563","display_name":"Q-learning","level":3,"score":0.26510000228881836},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.26409998536109924},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2628999948501587},{"id":"https://openalex.org/C12362212","wikidata":"https://www.wikidata.org/wiki/Q728435","display_name":"Linear subspace","level":2,"score":0.26100000739097595},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26080000400543213},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.2556000053882599}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:doi:10.48550/arxiv.2602.08616","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"pmh:oai:ris.utwente.nl:openaire/db0e95c1-4020-4f59-b7f6-48da88135b8f","is_oa":true,"landing_page_url":"https://research.utwente.nl/en/publications/db0e95c1-4020-4f59-b7f6-48da88135b8f","pdf_url":null,"source":{"id":"https://openalex.org/S4406922991","display_name":"University of Twente Research Information","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":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Hoppe, H, Akkerman, F, van Heeswijk, W & Schiffer, M 2026 'Breaking the Grid : Distance-Guided Reinforcement Learning in Large Discrete and Hybrid Action Spaces' ArXiv.org. https://doi.org/10.48550/arXiv.2602.08616","raw_type":"info:eu-repo/semantics/preprint"},{"id":"doi:10.48550/arxiv.2602.08616","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.08616","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2602.08616","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Reinforcement":[0,51],"Learning":[1,52],"is":[2],"increasingly":[3],"applied":[4],"to":[5,63,71,83,123,138],"logistics,":[6],"scheduling,":[7],"and":[8,59,115,145,154],"recommender":[9],"systems,":[10],"but":[11],"standard":[12],"algorithms":[13,27],"struggle":[14],"with":[15,69],"the":[16],"curse":[17],"of":[18,136],"dimensionality":[19],"in":[20,42,67],"such":[21],"large":[22],"discrete":[23],"action":[24,112,126],"spaces.":[25],"Existing":[26],"typically":[28],"rely":[29],"on":[30],"restrictive":[31],"grid-based":[32],"structures":[33],"or":[34,44],"computationally":[35],"expensive":[36],"nearest-neighbor":[37],"searches,":[38],"limiting":[39],"their":[40],"effectiveness":[41],"high-dimensional":[43],"irregularly":[45,146],"structured":[46,147],"domains.":[47],"We":[48,132],"propose":[49],"Distance-Guided":[50],"(DGRL),":[53],"combining":[54],"Sampled":[55],"Dynamic":[56],"Neighborhoods":[57],"(SDN)":[58],"Distance-Based":[60],"Updates":[61],"(DBU)":[62],"enable":[64],"efficient":[65],"RL":[66],"spaces":[68,127],"up":[70,137],"10$^\\text{20}$":[72],"actions.":[73],"Unlike":[74],"prior":[75],"methods,":[76],"SDN":[77],"leverages":[78],"a":[79,93,104],"semantic":[80],"embedding":[81],"space":[82,113],"perform":[84],"stochastic":[85],"volumetric":[86],"exploration,":[87],"provably":[88],"providing":[89],"full":[90],"support":[91],"over":[92],"local":[94],"trust":[95],"region.":[96],"Complementing":[97],"this,":[98],"DBU":[99],"transforms":[100],"policy":[101,118],"optimization":[102],"into":[103],"stable":[105],"regression":[106],"task,":[107],"decoupling":[108],"gradient":[109],"variance":[110],"from":[111],"cardinality":[114],"guaranteeing":[116],"monotonic":[117],"improvement.":[119],"DGRL":[120],"naturally":[121],"generalizes":[122],"hybrid":[124],"continuous-discrete":[125],"without":[128],"requiring":[129],"hierarchical":[130],"dependencies.":[131],"demonstrate":[133],"performance":[134],"improvements":[135],"66%":[139],"against":[140],"state-of-the-art":[141],"benchmarks":[142],"across":[143],"regularly":[144],"environments,":[148],"while":[149],"simultaneously":[150],"improving":[151],"convergence":[152],"speed":[153],"computational":[155],"complexity.":[156]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2026-02-11T00:00:00"}