論文

査読有り
2010年7月

CHR(PRISM)-based probabilistic logic learning

THEORY AND PRACTICE OF LOGIC PROGRAMMING
  • Jon Sneyers
  • ,
  • Wannes Meert
  • ,
  • Joost Vennekens
  • ,
  • Yoshitaka Kameya
  • ,
  • Taisuke Sato

10
開始ページ
433
終了ページ
447
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1017/S1471068410000207
出版者・発行元
CAMBRIDGE UNIV PRESS

PRISM is an extension of Prolog with probabilistic predicates and built-in support for expectation-maximization learning. Constraint Handling Rules (CHR) is a high-level programming language based on multi-headed multiset rewrite rules.
In this paper, we introduce a new probabilistic logic formalism, called CHRiSM, based on a combination of CHR and PRISM. It can be used for high-level rapid prototyping of complex statistical models by means of "chance rules". The underlying PRISM system can then be used for several probabilistic inference tasks, including probability computation and parameter learning. We define the CHRiSM language in terms of syntax and operational semantics, and illustrate it with examples. We define the notion of ambiguous programs and define a distribution semantics for unambiguous programs. Next, we describe an implementation of CHRiSM, based on CH R(PRISM). We discuss the relation between CHRiSM and other probabilistic logic programming languages, in particular PCHR. Finally, we identify potential application domains.

リンク情報
DOI
https://doi.org/10.1017/S1471068410000207
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000280508200006&DestApp=WOS_CPL
ID情報
  • DOI : 10.1017/S1471068410000207
  • ISSN : 1471-0684
  • Web of Science ID : WOS:000280508200006

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