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This book provides 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.
This book summarizes an exciting approach to knowledge-rich natural language understanding, in the context of language - using AI agents. Anyone interested in building cognitive systems that use language should read this book.
About the Authors:
- Marjorie McShane and Sergei Nirenburg are on the faculty of the Cognitive Science Department at Rensselaer Polytechnic Institute
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