Linguistics for the age of AI | Kementerian Pendidikan Dasar dan Menengah

Search by :

ALL Author Subject ISBN/ISSN Advanced Search

Last search:

Text

Linguistics for the age of AI

McShane, Marjorie - Personal Name; Nirenburg, Sergei - Personal Name;

A human-inspired, linguistically sophisticated model of language understanding for intelligent agent systems. One of the original goals of artificial intelligence research was to endow intelligent agents with human-level natural language capabilities. Recent AI research, however, has focused on applying statistical and machine learning approaches to big data rather than attempting to model what people do and how they do it. In this book, Marjorie McShane and Sergei Nirenburg return to the original goal of recreating human-level intelligence in a machine. They present a human-inspired, linguistically sophisticated model of language understanding for intelligent agent systems that emphasizes meaning—the deep, context-sensitive meaning that a person derives from spoken or written language. With Linguistics for the Age of AI, McShane and Nirenburg offer a roadmap for creating language-endowed intelligent agents (LEIAs) that can understand,explain, and learn. They describe the language-understanding capabilities of LEIAs from the perspectives of cognitive modeling and system building, emphasizing “actionability”—which involves achieving interpretations that are sufficiently deep, precise, and confident to support reasoning about action. After detailing their microtheories for topics such as semantic analysis, basic coreference, and situational reasoning, McShane and Nirenburg turn to agent applications developed using those microtheories and evaluations of a LEIA\\\'s language understanding capabilities. McShane and Nirenburg argue that the only way to achieve human-level language understanding by machines is to place linguistics front and center, using statistics and big data as contributing resources. They lay out a long-term research program that addresses linguistics and real-world reasoning together, within a comprehensive cognitive architecture.

Availability

No copy data

Detail Information

Series Title: -
Call Number: 401 McS l
Publisher: Cambridge : The MIT Press., 2021
Collation: xiii, 429 p.
Language: English
ISBN/ISSN: 9780262363136
Classification: 401
Content Type: -
Media Type: -
Carrier Type: -
Edition: -
Subject(s): Linguistics
Machine learning
lexicography
Specific Detail Info: -
Statement of Responsibility: -

Other version/related

No other version available

File Attachment

9780262363136
Other Resource Link

Comments

You must be logged in to post a comment