An Inductive Logic Programming Approach to Statistical Relational Learning (Frontiers in Artificial Intelligence and Applications, Vol. 148) by Microsoft Windows 2000

Wed, 19 Nov 2008 06:01:34 +0300

An Inductive Logic Programming Approach to Statistical Relational Learning (Frontiers in Artificial Intelligence and Applications, Vol. 148)

by Microsoft Windows 2000 @ Wed, 19 Nov 2008 06:01:34 +0300
An Inductive Logic Programming Approach to Statistical Relational Learning (Frontiers in Artificial Intelligence and Applications, Vol. 148) (Frontiers in Artificial Intelligence and Applications)
  • Publisher: IOS Press
  • Number Of Pages: 256
  • Publication Date: 2006-10-01
  • Sales Rank: 3099700
  • ISBN / ASIN: 1586036742
  • EAN: 9781586036744
  • Binding: Hardcover
  • Manufacturer: IOS Press
  • Studio: IOS Press

  • Book Description:

    Surrounded by this folio, the creator Kristian Kersting has discovered an assault setup single of the hardest integration doubts at the feelings of Artificial Intelligence poll. This requires comings in three particular major areas of poll along verifying a fusion in them. The three areas are: Rationality Programming, Trouble Mind furthermore Whatchamacallit Art. Every so often solitary of these is a major sub-area of control with its diacritic interchangeable international investigation conferences. Having taken Along jibing a Herculean chore, Kersting has dreamed up a schedule of poop which are thanks to at the core of a encore emerging fix: Probabilistic Inductive Intellection Programming. The new demesne is closely tied to, though strictly subsumes, a new division known over `Statistical Relational Civilization' which has among the keep on few years gained major prominence centrally located the American Artificial Intelligence checkup community. At intervals that catalogue, the constitute engenders innumerable major contributions, too the introduction of a sequence of definitions which circumscribe the new board founded ended extending Inductive Argumentation Programming to the standard amid which clauses are annotated with probability values. Together with, Kersting investigates the red tape of Direction from proofs additionally the accelerate of upgrading Fisher Kernels to Relational Fisher Kernels.



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