liu.seSearch for publications in DiVA
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
A Survey of Current Techniques for Reinforcement Learning
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.ORCID iD: 0000-0002-9267-2191
n/a.
1992 (English)Report (Other academic)
Abstract [en]

This survey considers response generating systems that improve their behaviour using reinforcement learning. The difference between unsupervised learning, supervised learning, and reinforcement learning is described. Two general problems concerning learning systems are presented; the credit assignment problem and the problem of perceptual aliasing. Notations and some general issues concerning reinforcement learning systems are presented. Reinforcement learning systems are further divided into two main classes; memory mapping and projective mapping systems. Each of these classes is described and some examples are presented. Some other approaches are mentioned that do not fit into the two main classes. Finally some issues not covered by the surveyed articles are discussed, and some comments on the subject are made.

Place, publisher, year, edition, pages
Linköping, Sweden: Linköping University, Department of Electrical Engineering , 1992. , 32 p.
Series
LiTH-ISY-I, ISSN 8765-4321 ; 1391
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-53392ISRN: LiTH-ISY-I-1391OAI: oai:DiVA.org:liu-53392DiVA: diva2:288303
Available from: 2010-01-20 Created: 2010-01-20 Last updated: 2014-10-08Bibliographically approved

Open Access in DiVA

fulltext(239 kB)337 downloads
File information
File name FULLTEXT01.pdfFile size 239 kBChecksum SHA-512
7ec4937c53ba15c6e3ab39f5fc4ac105546693350ab77285f72f79b89e456534402e688d3702e4d3e6042630de3962056573ab44dbe539d539689f41a115efe3
Type fulltextMimetype application/pdf

Authority records BETA

Borga, Magnus

Search in DiVA

By author/editor
Borga, Magnus
By organisation
Computer VisionThe Institute of Technology
Engineering and Technology

Search outside of DiVA

GoogleGoogle Scholar
Total: 337 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 639 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf