{"id":"https://openalex.org/W7160653664","doi":"https://doi.org/10.48550/arxiv.2605.06595","title":"Cross-Modal Navigation with Multi-Agent Reinforcement Learning","display_name":"Cross-Modal Navigation with Multi-Agent Reinforcement Learning","publication_year":2026,"publication_date":"2026-05-07","ids":{"openalex":"https://openalex.org/W7160653664","doi":"https://doi.org/10.48550/arxiv.2605.06595"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.06595","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.06595","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":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.06595","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135716606","display_name":"Shuo Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Shuo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015851859","display_name":"X. Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Xinzichen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5033129735","display_name":"Christopher Amato","orcid":"https://orcid.org/0000-0002-6786-7384"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Amato, Christopher","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":[],"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.6646000146865845,"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"}},"topics":[{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.6646000146865845,"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/T12032","display_name":"Multisensory perception and integration","score":0.07900000363588333,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10914","display_name":"Tactile and Sensory Interactions","score":0.05040000006556511,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7649000287055969},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.6521999835968018},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.6218000054359436},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.5896999835968018},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5619999766349792},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.5425000190734863},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.46560001373291016},{"id":"https://openalex.org/keywords/embodied-cognition","display_name":"Embodied cognition","score":0.4325999915599823}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7649000287055969},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.715399980545044},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.6521999835968018},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.6218000054359436},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.5896999835968018},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5619999766349792},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.5425000190734863},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5288000106811523},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.5171999931335449},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.46560001373291016},{"id":"https://openalex.org/C100609095","wikidata":"https://www.wikidata.org/wiki/Q1335050","display_name":"Embodied cognition","level":2,"score":0.4325999915599823},{"id":"https://openalex.org/C66882249","wikidata":"https://www.wikidata.org/wiki/Q169336","display_name":"Homogeneous","level":2,"score":0.3700999915599823},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.36149999499320984},{"id":"https://openalex.org/C103683099","wikidata":"https://www.wikidata.org/wiki/Q5370102","display_name":"Embodied agent","level":3,"score":0.33399999141693115},{"id":"https://openalex.org/C2776010242","wikidata":"https://www.wikidata.org/wiki/Q4677575","display_name":"Active perception","level":3,"score":0.33340001106262207},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3262999951839447},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.3073999881744385},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3012999892234802},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.28949999809265137},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.2777999937534332},{"id":"https://openalex.org/C2777891301","wikidata":"https://www.wikidata.org/wiki/Q3475123","display_name":"Navigation system","level":2,"score":0.2651999890804291},{"id":"https://openalex.org/C48677424","wikidata":"https://www.wikidata.org/wiki/Q6888088","display_name":"Mode (computer interface)","level":2,"score":0.2639999985694885},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.2619999945163727},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.26100000739097595},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.25440001487731934}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.06595","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.06595","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":"doi:10.48550/arxiv.2605.06595","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.06595","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":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"score":0.4783531725406647,"id":"https://metadata.un.org/sdg/17","display_name":"Partnerships for the goals"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Robust":[0],"embodied":[1],"navigation":[2,99,125,142],"relies":[3],"on":[4,97],"complementary":[5,134],"sensory":[6],"cues.":[7],"However,":[8],"high-quality":[9],"and":[10,35,55,88,108,139,141,152],"well-aligned":[11],"multi-modal":[12,30,91,150],"data":[13],"is":[14,25,121,136],"often":[15],"difficult":[16],"to":[17],"obtain":[18],"in":[19,143],"practice.":[20],"Training":[21],"a":[22,48,71,89],"monolithic":[23],"model":[24,154],"also":[26],"challenging":[27],"as":[28],"rich":[29],"inputs":[31],"induce":[32],"complex":[33,145],"representations":[34],"substantially":[36],"enlarge":[37],"the":[38,60],"policy":[39],"space.":[40],"Cross-modal":[41],"collaboration":[42,82,117,130],"among":[43,131],"lightweight":[44],"modality-specialized":[45],"agents":[46,132],"offers":[47],"scalable":[49],"paradigm.":[50],"It":[51],"enables":[52],"flexible":[53],"deployment":[54],"parallel":[56],"execution,":[57],"while":[58],"preserving":[59],"strength":[61],"of":[62],"each":[63],"modality.":[64],"In":[65],"this":[66],"paper,":[67],"we":[68],"propose":[69],"\\textbf{CRONA},":[70],"Multi-Agent":[72],"Reinforcement":[73],"Learning":[74],"(MARL)":[75],"framework":[76],"for":[77,123],"\\textbf{Cro}ss-Modal":[78],"\\textbf{Na}vigation.":[79],"CRONA":[80],"improves":[81],"by":[83],"leveraging":[84],"control-relevant":[85],"auxiliary":[86],"beliefs":[87],"centralized":[90],"critic":[92],"with":[93,118,133],"global":[94],"state.":[95],"Experiments":[96],"visual-acoustic":[98],"tasks":[100],"show":[101],"that":[102,115],"multi-agent":[103],"methods":[104],"significantly":[105],"improve":[106],"performance":[107],"efficiency":[109],"over":[110],"single-agent":[111],"baselines.":[112],"We":[113],"find":[114],"homogeneous":[116],"limited":[119],"modalities":[120,135],"sufficient":[122],"short-range":[124],"under":[126],"salient":[127],"cues;":[128],"heterogeneous":[129],"generally":[137],"efficient":[138],"effective;":[140],"large,":[144],"environments":[146],"requires":[147],"both":[148],"richer":[149],"perception":[151],"increased":[153],"capacity.":[155]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-09T00:00:00"}