| 书目名称 | Probabilistic Logic Networks | | 副标题 | A Comprehensive Fram | | 编辑 | Ben Goertzel,Matthew‘Iklé,Ari Heljakka | | 视频video | | | 概述 | Provides a comprehensive framework for uncertain reasoning, integrating probability theory, predicate and term logic, and pattern theory.Considers a broad scope of reasoning types.Fuses rigorous mathe | | 图书封面 |  | | 描述 | 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. First of all, we hold to a philosophical perspective in which “reasoning” – properly understood – plays a central role in cognitive activity. We realize that other perspectives exist; in particular, logical reasoning is sometimes construed as a special kind of cognition that humans carry out only occasionally, as a deviation from their usual (intuitive, emotional, pragmatic, sensorimotor, etc.) modes of thought. However, we consider this alternati | | 出版日期 | Book 2009 | | 关键词 | Fuzzy; experiential semantics; first-order extensional inference; higher-order extensional inference; in | | 版次 | 1 | | doi | https://doi.org/10.1007/978-0-387-76872-4 | | isbn_softcover | 978-1-4419-4578-5 | | isbn_ebook | 978-0-387-76872-4 | | copyright | Springer-Verlag US 2009 |
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发表于 2025-3-21 19:37:55
