This book presents a model of language understanding for intelligent agent systems that is human-inspired and linguistically complex.
Giving intelligent agents human-level natural language skills was one of the initial aims of artificial intelligence research. However, rather than aiming to simulate what humans do and how they do it, recent AI research has concentrated on applying statistical and machine learning methodologies to massive data.
Marjorie McShane and Sergei Nirenburg go back to their initial objective of giving machine human-level intelligence in this book. They provide a model of language comprehension for intelligent agent systems that are linguistically sophisticated, and human-inspired, and place an emphasis on meaning—the rich, context-specific meaning that a person obtains from spoken or written language.
The intriguing method for knowledge-rich natural language interpretation is summarized in this book employing AI agents. This book should be read by everyone with an interest in creating language-based cognitive systems.
