ROBUST, SCALABLE AND GENERALIZABLE MACHINE LEARNING PARADIGM FOR MULTI-AGENT APPLICATIONS

Described is a learning system for multi-agent applications. In operation, the system initializes a plurality of learning agents. The learning agents include both tactical agents and strategic agents. The strategic agents take an observation from an environment and select one or more of the tactical...

Full description

Saved in:
Bibliographic Details
Main Authors Soleyman, Sean, Khosla, Deepak
Format Patent
LanguageEnglish
Published 10.09.2020
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
Online AccessGet full text

Cover

Abstract Described is a learning system for multi-agent applications. In operation, the system initializes a plurality of learning agents. The learning agents include both tactical agents and strategic agents. The strategic agents take an observation from an environment and select one or more of the tactical agents to produce an action that is used to control a platform's actuators or simulated movements in the environment to complete a task. Alternatively, the tactical agents produce the action corresponding to a learned low-level behavior to control the platform's actuators or simulated movements in the environment to complete the task.
AbstractList Described is a learning system for multi-agent applications. In operation, the system initializes a plurality of learning agents. The learning agents include both tactical agents and strategic agents. The strategic agents take an observation from an environment and select one or more of the tactical agents to produce an action that is used to control a platform's actuators or simulated movements in the environment to complete a task. Alternatively, the tactical agents produce the action corresponding to a learned low-level behavior to control the platform's actuators or simulated movements in the environment to complete the task.
Author Soleyman, Sean
Khosla, Deepak
Author_xml – fullname: Soleyman, Sean
– fullname: Khosla, Deepak
BookMark eNqNi70KwjAURjPo4N87XHC14A8FO96maXohTUqSDrqUInGStFDfH4v4APINBw7nW7NFHGJYsZs1eev8ARxHhbkSgLoAKbSwqOj-NTXyirQAJdBq0hIatFiQrKE0FupWeUpwvnjAplHE0ZPRbsuWz_41hd2PG7YvhedVEsahC9PYP0IM76515-O8a5plKZ4u_1UfCKE0Dw
ContentType Patent
DBID EVB
DatabaseName esp@cenet
DatabaseTitleList
Database_xml – sequence: 1
  dbid: EVB
  name: esp@cenet
  url: http://worldwide.espacenet.com/singleLineSearch?locale=en_EP
  sourceTypes: Open Access Repository
DeliveryMethod fulltext_linktorsrc
Discipline Medicine
Chemistry
Sciences
Physics
ExternalDocumentID US2020285995A1
GroupedDBID EVB
ID FETCH-epo_espacenet_US2020285995A13
IEDL.DBID EVB
IngestDate Fri Jul 19 12:49:55 EDT 2024
IsOpenAccess true
IsPeerReviewed false
IsScholarly false
Language English
LinkModel DirectLink
MergedId FETCHMERGED-epo_espacenet_US2020285995A13
Notes Application Number: US202016792869
OpenAccessLink https://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20200910&DB=EPODOC&CC=US&NR=2020285995A1
ParticipantIDs epo_espacenet_US2020285995A1
PublicationCentury 2000
PublicationDate 20200910
PublicationDateYYYYMMDD 2020-09-10
PublicationDate_xml – month: 09
  year: 2020
  text: 20200910
  day: 10
PublicationDecade 2020
PublicationYear 2020
RelatedCompanies HRL Laboratories, LLC
RelatedCompanies_xml – name: HRL Laboratories, LLC
Score 3.2779152
Snippet Described is a learning system for multi-agent applications. In operation, the system initializes a plurality of learning agents. The learning agents include...
SourceID epo
SourceType Open Access Repository
SubjectTerms CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
Title ROBUST, SCALABLE AND GENERALIZABLE MACHINE LEARNING PARADIGM FOR MULTI-AGENT APPLICATIONS
URI https://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20200910&DB=EPODOC&locale=&CC=US&NR=2020285995A1
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV3dS8MwED_G_HzTqfgxJaD0yWJn2219GJJ-bKu0XemHzL2MtrYgSDdcxX_fS-jmnvaW3JEjCVxyv8vdBeChm2SylPUkUVNVWVSSPBFTNGPFoqthGxFRobF8Z9frjmPldapOG_C1zoXhdUJ_eXFE1KgM9b3i5_Xy34ll8tjK1VP6iaTFyzAamEKNjpmrvyMJpj6w_Ik5MQTDGMSh4AWcx2q1aSpFrLTHDGlWad9601leynL7UhmewL6P8srqFBp52YIjY_33WgsO3frJuwUHPEYzWyGx1sPVGbwHEz0Oo0cSGtShumMR6pmkDkOzZ5ziUmNsexZxLBp4tjciPg2oaY9cgsCPuLET2SLFIRGhvr9JKD6H-6EVGWMRZzvfbM48DreXJl9As1yU-SUQNe2niE-UD1mRFTSLtCxReqkm5Wk_U4vn4grauyRd72bfwDHrssiJjtSGZvX9k9_i9Vyld3xX_wCS2YsW
link.rule.ids 230,309,786,891,25594,76906
linkProvider European Patent Office
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV3dS8MwED_G_JhvOhU_pgaUPlnsbLutD0PSj63VNiv9kOnLaGsLgnTDVfz3TUI397S3cEeO5OBy90vuLgB3vSSTpawviZqqyqKS5ImY0jBWLHoaHVNEVGis3tkjPTtWnqfqtAFfq1oY3if0lzdHpBaVUXuv-Hm9-L_EMnlu5fIh_aSk-dMoGppCjY7ZVX9XEkx9aPkTc2IIhjGMQ4EEnMd6tWkqplhpp8_687Lg6VVndSmLTacyOoRdn8orqyNo5GUbWsbq77U27Hv1k3cb9niOZrakxNoOl8fwFkz0OIzuUWhgF-uuhTAxUZ2G5rxziocN2yEWci0cEIeMkY8DbDpjD1Hgh7zYjRwR0ykRwr6_Lig-gduRFRm2SFc7WytnFoebW5NPoVnOy_wMkJoOUopPlA9ZkRUaFmlZovRTTcrTQaYWj8U5dLZJutjOvoGWHXnuzHXIyyUcMBbLouhKHWhW3z_5FXXVVXrNNfwHPXmOAw
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Apatent&rft.title=ROBUST%2C+SCALABLE+AND+GENERALIZABLE+MACHINE+LEARNING+PARADIGM+FOR+MULTI-AGENT+APPLICATIONS&rft.inventor=Soleyman%2C+Sean&rft.inventor=Khosla%2C+Deepak&rft.date=2020-09-10&rft.externalDBID=A1&rft.externalDocID=US2020285995A1