{"id":"https://openalex.org/W7160619993","doi":"https://doi.org/10.48550/arxiv.2605.05951","title":"HaM-World: Soft-Hamiltonian World Models with Selective Memory for Planning","display_name":"HaM-World: Soft-Hamiltonian World Models with Selective Memory for Planning","publication_year":2026,"publication_date":"2026-05-07","ids":{"openalex":"https://openalex.org/W7160619993","doi":"https://doi.org/10.48550/arxiv.2605.05951"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.05951","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.05951","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.2605.05951","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135646632","display_name":"Haoyun Tang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tang, Haoyun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135652334","display_name":"Haodong Cui","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cui, Haodong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022456722","display_name":"Keyao Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Keyao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135715806","display_name":"Kun Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Kun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135663556","display_name":"Zhandong Mei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mei, Zhandong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.474700003862381,"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":0.474700003862381,"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/T10906","display_name":"AI-based Problem Solving and Planning","score":0.09539999812841415,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.07280000299215317,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/subspace-topology","display_name":"Subspace topology","score":0.5428000092506409},{"id":"https://openalex.org/keywords/bounded-function","display_name":"Bounded function","score":0.5374000072479248},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.4715000092983246},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4431000053882599},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.37380000948905945},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.34549999237060547},{"id":"https://openalex.org/keywords/partially-observable-markov-decision-process","display_name":"Partially observable Markov decision process","score":0.3375999927520752},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.320499986410141}],"concepts":[{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.5428000092506409},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5428000092506409},{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.5374000072479248},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.4715000092983246},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4431000053882599},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41499999165534973},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.37380000948905945},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.34549999237060547},{"id":"https://openalex.org/C17098449","wikidata":"https://www.wikidata.org/wiki/Q176814","display_name":"Partially observable Markov decision process","level":4,"score":0.3375999927520752},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.320499986410141},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3028999865055084},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.2946000099182129},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.29190000891685486},{"id":"https://openalex.org/C79581498","wikidata":"https://www.wikidata.org/wiki/Q1367530","display_name":"Suite","level":2,"score":0.2858999967575073},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2768999934196472},{"id":"https://openalex.org/C28761237","wikidata":"https://www.wikidata.org/wiki/Q7805321","display_name":"Time horizon","level":2,"score":0.2768000066280365},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.2766000032424927},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.2727999985218048},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.26649999618530273},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.25920000672340393}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.05951","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.05951","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.2605.05951","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.05951","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":0.46047741174697876,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"World":[0],"models":[1],"enable":[2],"model-based":[3],"planning":[4,16],"through":[5,97],"learned":[6],"latent":[7,63,89,121],"dynamics,":[8,106],"but":[9],"imagined":[10,129],"rollouts":[11],"become":[12],"unstable":[13],"as":[14,82],"the":[15,20,62,83,87,117,143,182,222],"horizon":[17],"grows":[18],"or":[19],"dynamics":[21,125,173,225],"distribution":[22],"shifts.":[23],"We":[24,52],"argue":[25],"that":[26,45,60],"this":[27,92],"instability":[28],"reflects":[29],"two":[30],"missing":[31],"structures":[32],"in":[33,164,185],"planner-facing":[34],"latents:":[35],"history-conditioned":[36,84],"memory":[37,81],"for":[38],"approximate":[39],"Markov":[40],"completeness,":[41],"and":[42,49,71,112,131,160,177,197,216],"geometric":[43],"organization":[44],"separates":[46],"configuration,":[47],"momentum,":[48],"task":[50],"semantics.":[51],"propose":[53],"HaM-World":[54,141,180],"(HMW),":[55],"a":[56,66,72,119,156],"structured":[57,210],"world":[58],"model":[59],"decomposes":[61],"state":[64,122],"into":[65],"canonical":[67],"(q,":[68,94],"p)":[69,95],"subspace":[70,74],"context":[73],"c,":[75],"while":[76,107],"using":[77],"Mamba":[78],"selective":[79],"state-space":[80],"input":[85],"to":[86,153],"same":[88],"dynamics.":[90],"Within":[91],"interface,":[93],"evolves":[96],"an":[98],"energy-derived":[99],"Hamiltonian":[100],"vector":[101],"field":[102],"plus":[103],"learnable":[104],"residual/control":[105],"c":[108],"captures":[109],"semantic,":[110],"dissipative,":[111],"non-conservative":[113],"factors.":[114],"This":[115],"gives":[116],"planner":[118],"single":[120],"shared":[123],"by":[124],"prediction,":[126],"reward/value":[127],"estimation,":[128],"rollouts,":[130,215],"CEM":[132],"action":[133,175],"search.":[134],"On":[135],"four":[136],"DeepMind":[137],"Control":[138],"Suite":[139],"tasks,":[140],"reaches":[142],"highest":[144,183],"Avg.":[145],"AUC":[146],"(117.9,":[147],"+9.5%),":[148],"reduces":[149],"long-horizon":[150],"rollout":[151],"error":[152],"45%":[154],"of":[155,192],"strong":[157],"baseline":[158],"model,":[159],"wins":[161],"11/12":[162],"k":[163],"{3,5,7}":[165],"MSE":[166],"cells.":[167],"Under":[168],"12":[169],"OOD":[170],"perturbations":[171],"spanning":[172],"shifts,":[174],"delay,":[176],"observation":[178],"masking,":[179],"achieves":[181],"return":[184],"every":[186],"condition,":[187],"with":[188],"average":[189],"OOD-return":[190],"gains":[191],"10.2%":[193],"on":[194,199],"Finger":[195],"Spin":[196],"13.6%":[198],"Reacher":[200],"Easy.":[201],"Mechanism":[202],"diagnostics":[203],"further":[204],"show":[205],"bounded":[206],"action-free":[207],"Hamiltonian-energy":[208],"drift,":[209],"energy":[211,219],"variation":[212],"under":[213],"policy":[214],"coherent":[217],"control-induced":[218],"transfer,":[220],"supporting":[221],"intended":[223],"Soft-Hamiltonian":[224],"design.":[226]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-09T00:00:00"}
