License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/DagSemProc.10302.6
URN: urn:nbn:de:0030-drops-28014
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2010/2801/
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Toussaint, Marc

Why deterministic logic is hard to learn but Statistical Relational Learning works

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10302.ToussaintMarc.ExtAbstract.2801.pdf (0.4 MB)

Abstract

A brief note on why we think that the statistical relational learning framework is a great advancement over deterministic logic -- in particular in the context of model-based Reinforcement Learning.

BibTeX - Entry

@InProceedings{toussaint:DagSemProc.10302.6,
  author =	{Toussaint, Marc},
  title =	{{Why deterministic logic is hard to learn but Statistical Relational Learning works}},
  booktitle =	{Learning paradigms in dynamic environments},
  pages =	{1--2},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2010},
  volume =	{10302},
  editor =	{Barbara Hammer and Pascal Hitzler and Wolfgang Maass and Marc Toussaint},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2010/2801},
  URN =		{urn:nbn:de:0030-drops-28014},
  doi =		{10.4230/DagSemProc.10302.6},
  annote =	{Keywords: Statistical relational learning, relational model-based Reinforcement Learning}
}

Keywords: Statistical relational learning, relational model-based Reinforcement Learning
Collection: 10302 - Learning paradigms in dynamic environments
Issue Date: 2010
Date of publication: 05.11.2010

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