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 …

Explanation-based learning (EBL) is a technique by which an intelligent system can learn by
observing examples. EBL systems are characterized by the ability to create justified …

In order to solve problems effectively, a problem solver must be able to exploit domain-
specific search control knowledge. Although previous research has demonstrated that …

Strategic knowledge is used by an agent to decide what action to perform next, where
actions have consequences external to the agent. This article presents a computer-mediated …

The ability to learn from experience is a fundamental requirement for intelligence. One of the
most basic characteristics of human intelligence is that people can learn from problem …

This article outlines explanation-based learning (EBL) and its role in improving problem
solving performance through experience. Unlike inductive systems, which learn by …

This book is the third volume in a series that provides a hands-on perspective on the
evolving theories associated with Roger Schank and his students. The primary focus of this …

Traditional learning-from-examples methods assume that examples are given beforehand
and all features are measured for each example. However, in many robotic domains the …

The Acquisition of Strategic Knowledge deals with the automation of the acquisition of
strategic knowledge and describes a knowledge acquisition program called ASK, which …

Psychology and philosophy have long studied the nature and role of explanation. More
recently, artificial intelligence research has developed promising theories of how …