hh.sePublikationer
Ändra sökning
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Learning to evaluate conditional partial plans
Department of Computer Science, Lund University, Sweden.ORCID-id: 0000-0002-7796-5201
Department of Computer Science, Lund University, Sweden.
2007 (Engelska)Ingår i: ICMLA 2007: Sixth International Conference on Machine Learning and Applications : proceedings : 13-15 Dec. 2007, Cincinnati, Ohio, USA, Los Alamitos, Calif.: IEEE Computer Society, 2007, s. 235-240Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

We study agents situated in partially observable environments, who do not have sufficient resources to create conformant plans. Instead, they generate plans which are conditional and partial, execute or simulate them, and learn to evaluate their quality from experience. Our agent employs an incomplete symbolic deduction system based on Active Logic and Situation Calculus for reasoning about actions and their consequences. An Inductive Logic Programming algorithm generalises observations and deduced knowledge, allowing the agent to execute a good plan. We show results of using PROGOL learning algorithm to distinguish "bad" plans early in the reasoning process, before too many resources are wasted on considering them. We show that additional knowledge needs to be provided before learning can be successful, but argue that the benefits achieved make it worthwhile. Finally, we identify several assumptions made by PROGOL, shared by other similarly universal algorithms, which are well justified in general, but fail to exploit the properties of the class of problems faced by rational agents.

Ort, förlag, år, upplaga, sidor
Los Alamitos, Calif.: IEEE Computer Society, 2007. s. 235-240
Nyckelord [en]
Agents, Artificial intelligence, Boolean functions, Computer programming, Education, Fuzzy logic, Learning systems, Logic programming, Quality control, Robot learning
Nationell ämneskategori
Datavetenskap (datalogi)
Identifikatorer
URN: urn:nbn:se:hh:diva-21029DOI: 10.1109/ICMLA.2007.101ISI: 000252793400039Scopus ID: 2-s2.0-47349091660ISBN: 978-0-7695-3069-7 ISBN: 0-7695-3069-9 OAI: oai:DiVA.org:hh-21029DiVA, id: diva2:587664
Konferens
Sixth International Conference on Machine Learning and Applications, 13-15 Dec. 2007, Cincinnati, Ohio, USA
Tillgänglig från: 2013-01-14 Skapad: 2013-01-14 Senast uppdaterad: 2018-01-11Bibliografiskt granskad

Open Access i DiVA

Fulltext saknas i DiVA

Övriga länkar

Förlagets fulltextScopus

Personposter BETA

Nowaczyk, Sławomir

Sök vidare i DiVA

Av författaren/redaktören
Nowaczyk, Sławomir
Datavetenskap (datalogi)

Sök vidare utanför DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetricpoäng

doi
isbn
urn-nbn
Totalt: 127 träffar
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf