本书共16 章. 第1~ 6 章讨论人工智能的认知问题和逻辑基础, 论述约束推理, 定性推理,
基于范例推理, 概率推理. 第7~ 13 章重点讨论机器学习, 包括归纳学习, 支持向量机, 解释学习 …

Computational Intelligence comprises concepts, paradigms, algorithms, and
implementations of systems that are supposed to exhibit intelligent behavior in complex …

机器学习的研究不仅是人工智能研究的重要问题, 而且已成为计算机科学与技术的核心问题之一
. 智能决策支持系统是将人工智能技术引入决策支持系统而形成的一种新型信息系统 …

The purpose of this book is to provide an up-to-date and systematical introduction to the
principles and algorithms of machine learning. The definition of learning is broad enough to …

The Springer Handbook for Computational Intelligence is the first book covering the basics,
the state-of-the-art and important applications of the dynamic and rapidly expanding …

Traditional books on machine learning can be divided into two groups-those aimed at
advanced undergraduates or early postgraduates with reasonable mathematical knowledge …

This book is concerned with the concepts, the theories, and the algorithms of machine
learning. In Part I, we provide the fundamental knowledge about machine learning by …

This authoritative, expanded and updated second edition of Encyclopedia of Machine
Learning and Data Mining provides easy access to core information for those seeking entry …

Machine Learning: Discriminative and Generative covers the main contemporary themes
and tools in machine learning ranging from Bayesian probabilistic models to discriminative …

Machine Learning according to Michie et al (D. Michie, 1994) is generally taken to
encompass automatic computing procedures based on logical or binary operations that …