View in EDS

Analyzing RL components for Wagner’s framework via Brouwer’s conjecture.

Saved in:
Bibliographic Details
Title: Analyzing RL components for Wagner’s framework via Brouwer’s conjecture.
Authors: Angileri, Flora1, Lombardi, Giulia2, Fois, Andrea3, Faraone, Renato3, Metta, Carlo4, Salvi, Michele1, Bianchi, Luigi Amedeo2, Fantozzi, Marco3, Galfrè, Silvia Giulia5, Pavesi, Daniele3, Parton, Maurizio6, curiosailab@gmail.com, Morandin, Francesco3
Source: Machine Learning; Nov2025, Vol. 114 Issue 11, p1-24, 24p
Database: Applied Science & Technology Source
FullText Text:
  Availability: 0
Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 188439260
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Analyzing RL components for Wagner’s framework via Brouwer’s conjecture.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AU" term="%22Angileri%2C+Flora%22">Angileri, Flora</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AU" term="%22Lombardi%2C+Giulia%22">Lombardi, Giulia</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AU" term="%22Fois%2C+Andrea%22">Fois, Andrea</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AU" term="%22Faraone%2C+Renato%22">Faraone, Renato</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AU" term="%22Metta%2C+Carlo%22">Metta, Carlo</searchLink><relatesTo>4</relatesTo><br /><searchLink fieldCode="AU" term="%22Salvi%2C+Michele%22">Salvi, Michele</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AU" term="%22Bianchi%2C+Luigi+Amedeo%22">Bianchi, Luigi Amedeo</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AU" term="%22Fantozzi%2C+Marco%22">Fantozzi, Marco</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AU" term="%22Galfrè%2C+Silvia+Giulia%22">Galfrè, Silvia Giulia</searchLink><relatesTo>5</relatesTo><br /><searchLink fieldCode="AU" term="%22Pavesi%2C+Daniele%22">Pavesi, Daniele</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AU" term="%22Parton%2C+Maurizio%22">Parton, Maurizio</searchLink><relatesTo>6</relatesTo>, <i>curiosailab@gmail.com</i><br /><searchLink fieldCode="AU" term="%22Morandin%2C+Francesco%22">Morandin, Francesco</searchLink><relatesTo>3</relatesTo>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Machine+Learning%22">Machine Learning</searchLink>; Nov2025, Vol. 114 Issue 11, p1-24, 24p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=188439260
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1007/s10994-025-06890-2
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 24
        StartPage: 1
    Titles:
      – TitleFull: Analyzing RL components for Wagner’s framework via Brouwer’s conjecture.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Angileri, Flora
      – PersonEntity:
          Name:
            NameFull: Lombardi, Giulia
      – PersonEntity:
          Name:
            NameFull: Fois, Andrea
      – PersonEntity:
          Name:
            NameFull: Faraone, Renato
      – PersonEntity:
          Name:
            NameFull: Metta, Carlo
      – PersonEntity:
          Name:
            NameFull: Salvi, Michele
      – PersonEntity:
          Name:
            NameFull: Bianchi, Luigi Amedeo
      – PersonEntity:
          Name:
            NameFull: Fantozzi, Marco
      – PersonEntity:
          Name:
            NameFull: Galfrè, Silvia Giulia
      – PersonEntity:
          Name:
            NameFull: Pavesi, Daniele
      – PersonEntity:
          Name:
            NameFull: Parton, Maurizio
      – PersonEntity:
          Name:
            NameFull: Morandin, Francesco
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 11
              Text: Nov2025
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-print
              Value: 08856125
          Numbering:
            – Type: volume
              Value: 114
            – Type: issue
              Value: 11
          Titles:
            – TitleFull: Machine Learning
              Type: main
ResultId 1