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
Link To Document