Syntactic Networks--Kernel Memory Approach
Hoya, Tetsuya
- 出版商: Springer
- 出版日期: 2024-05-22
- 售價: $6,200
- 貴賓價: 9.5 折 $5,890
- 語言: 英文
- 頁數: 129
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 3031573110
- ISBN-13: 9783031573118
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商品描述
This book proposes a novel connectionist approach to a challenging topic of language modeling within the context of kernel memory and artificial mind system, both proposed previously by the author in the very first volume of the series, Artificial Mind System--Kernel Memory Approach: Studies in Computational Intelligence, Vol. 1. The present volume focuses on how syntactic structures of language are modeled in terms of the respective composite connectionist architectures, each embracing both the nonsymbolic and symbolic parts. These two parts are developed via inter-module processes within the artificial mind system and eventually integrated under a unified framework of kernel memory. The data representation by the networks embodied within the kernel memory principle is essentially local, unlike conventional artificial neural network models such as the pervasive multilayer perceptron-based neural networks. With this locality principle, kernel memory inherently bears many attractive features, such as topologically unconstrained network formation, straightforward network growing, shrinking, and reconfiguration, no requirement of arduous iterative parameter tuning, construction of transparent and hierarchical data structures, and multimodal and temporal data processing via the network representation. Exploiting these multifacet properties of kernel memory with interweaving the notion of inter-module processing within the artificial mind system provides coherent accounts for concept formation and how various linguistic phenomena, viz. word compoundings, morphologies, and multiword constructions, are modeled. The description is then extended to more intricate network models of context-dependent lexical network and syntactic-oriented processing, the latter being the central theme of the present study, and further to those representing a hybrid of nonverbal and verbal thinking, and semantic and pragmatic aspects of sentential meaning. The book is intended for general readers engaging in various areas of study in cognitive science, computer science, engineering, linguistics, philosophy, psycholinguistics, and psychology.
商品描述(中文翻譯)
本書提出了一種新穎的連接主義方法,用於在核心記憶和人工智能系統的背景下進行語言建模,這兩者都是作者在該系列的第一卷《人工智能系統-核心記憶方法:計算智能研究》中提出的。本卷主要關注如何以相應的複合連接主義架構來建模語言的句法結構,其中包括非符號和符號兩個部分。這兩個部分通過人工智能系統內的模塊間過程進行開發,最終在核心記憶的統一框架下進行整合。核心記憶原則中的網絡所體現的數據表示本質上是局部的,不同於常見的基於多層感知器的人工神經網絡模型。憑藉這種局部性原則,核心記憶本身具有許多吸引人的特點,例如拓撲無限制的網絡形成、簡單直觀的網絡增長、縮小和重構、無需繁瑣的迭代參數調整、透明和分層數據結構的構建,以及通過網絡表示進行多模態和時間數據處理。利用核心記憶的這些多面性特性,並將其與人工智能系統內的模塊間處理的概念交織在一起,可以對概念形成以及各種語言現象(如詞組合、形態和多詞組構造)的建模提供一致的解釋。然後,將描述擴展到更複雜的上下文相依詞彙網絡和句法導向處理的網絡模型,後者是本研究的核心主題,並進一步表示非語言和語言思維的混合,以及句子意義的語義和語用方面。本書面向從事認知科學、計算機科學、工程學、語言學、哲學、心理語言學和心理學等各個領域的一般讀者。