• DocumentCode
    1804435
  • Title

    Supplementing neural reinforcement learning with symbolic methods: Possibilities and challenges

  • Author

    Sun, Ron

  • Author_Institution
    NEC Res. Inst., Princeton, NJ, USA
  • Volume
    6
  • fYear
    1999
  • fDate
    36342
  • Firstpage
    4145
  • Abstract
    Several different ways of using symbolic methods to improve reinforcement learning are identified and discussed in some detail. Each demonstrates to some extent the advantages of combining reinforcement learning and symbolic methods. These methods point to the potentials and the challenges of this line of research
  • Keywords
    formal logic; learning (artificial intelligence); neural nets; RL; neural reinforcement learning; symbolic methods; Decision making; Learning systems; National electric code; Neural networks; Partitioning algorithms; Process planning; Space exploration; State-space methods; Sun; Usability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1999. IJCNN '99. International Joint Conference on
  • Conference_Location
    Washington, DC
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-5529-6
  • Type

    conf

  • DOI
    10.1109/IJCNN.1999.830828
  • Filename
    830828