Recurrent Neural Networks to Approximate the Semantics of Acceptable Logic Programs

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Recurrent Neural Networks to Approximate the Semantics of Acceptable Logic Programs

Steffen HölldoblerSteffen Hölldobler,  Yvonne KalinkeYvonne Kalinke,  Hans-Peter StörrHans-Peter Störr
Recurrent Neural Networks to Approximate the Semantics of Acceptable Logic Programs


Steffen Hölldobler, Yvonne Kalinke, Hans-Peter Störr
Recurrent Neural Networks to Approximate the Semantics of Acceptable Logic Programs
In J. Slaney G. Antoniou, eds., Advanced Topics in Artificial Intelligence - 11th Australian Joint Conference on Artifiial Intelligence (AI'98), volume 1502 of LNAI, 167-178, 1998. Springer
The final publication is available at Springer.
@inproceedings{HKS1998,
  author    = {Steffen H{\"{o}}lldobler and Yvonne Kalinke and Hans-Peter
               St{\"{o}}rr},
  title     = {Recurrent Neural Networks to Approximate the Semantics of
               Acceptable Logic Programs},
  editor    = {J. Slaney G. Antoniou},
  booktitle = {Advanced Topics in Artificial Intelligence - 11th Australian
               Joint Conference on Artifiial Intelligence (AI'98)},
  series    = {LNAI},
  volume    = {1502},
  publisher = {Springer},
  year      = {1998},
  pages     = {167-178}
}