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Cookie akzeptieren![Goertzel, Ben / Heljakka, Ari et al. Probabilistic Logic Networks - A Comprehensive Framework for Uncertain Inference. Springer US, 2008.](https://eichendorff21.de/cdata/ZQAZtA1EccHWI7b27pXvtxwRyas=/300x0/9780387768717.png)
Ben Goertzel / Ari Heljakka / Izabela Freire Goertzel / Matthew Iklé
Probabilistic Logic Networks
- Springer US
- 2008
- Gebunden
- 344 Seiten
- ISBN 9780387768717
Abstract In this chapter we provide an overview of probabilistic logic networks (PLN), including our motivations for developing PLN and the guiding principles underlying PLN. We discuss foundational choices we made, introduce PLN knowledge representation, and briefly introduce inference rules and truth- values. We also place PLN in context with other approaches to uncertain inference. 1.1 Motivations This book presents Probabilistic Logic Networks (PLN), a systematic and pragmatic framework for computationally carrying out uncertain reasoning - r- soning about uncertain data, and/or reasoning involving uncertain conclusions. We begin with a few comments about why we believe this is such an interesting and important domain of investigation.
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