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Features
Focuses on natural language, the carrier of knowledge and intelligence to study uncertainty in AI
Presents a cloud model illustrating the uncertain mechanism during the transformation between qualitative concepts and quantitative values
Demonstrates how the data field can be used in the clustering of data mining and complex network study
Explores the emergence of swarm intelligence based on cloud model and data field
Illustrates theories and concepts with applications like automatic driving, image segmentation, etc.
Summary
This book develops a framework that shows how uncertainty in Artificial Intelligence (AI) expands and generalizes traditional AI. It explores the uncertainties of knowledge and intelligence. The authors focus on the importance of natural language - the carrier of knowledge and intelligence, and introduce efficient physical methods for data mining amd control. In this new edition, we have more in-depth description of the models and methods, of which the mathematical properties are proved strictly which make these theories and methods more complete. The authors also highlight their latest research results.
Table of Contents
Chapter 1: Aritificial Intelligence Challenged by Uncertainty
Chapter 2: Cloud Model: a Cognitive Model for Qualitative and Quantitative Transformation
Chapter 3: Gaussian Cloud Tranformation
Chapter 4: Data Field and Topological Potential
Chapter 5: Reasoning and Control of Qualitative Knowledge
Chapter 6: Cognitive Physics for Swarm Intelligence
Chapter 7: Great Development of Artificial Intelligence with Uncertainty Due to Cloud Computing