From: Elric of Imrryr
Subject: FA: $2.00 ARTIFICIAL INTELLIGENCE - 2 Ed by Patrick Henry Wilson
Date: 
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ARTIFICIAL INTELLIGENCE - 2nd Edition
 by Patrick Henry Wilson

7"x9.5", hard cover, 525 pages, illustrated 
Publisher: Addison-Wesley 
Weight: 2 lbs. 
  

The first edition of Patrick Henry Winston's Artificial Intelligence is a 
classic. Now Professor Winston has completely revised the first edition, 
producing this comprehensive new book in which old material has been 
purged and new material added to bring things up to date. All surviving 
material has been rewritten and rearranged to improve clarity and 
coherence. 

The book explains the basic theoretical concepts of Artificial 
Intelligence in a style that is clear, concise and easy to understand.
In addition, it introduces readers to representative application-oriented 
ideas, conveying the excitement surrounding this stimulating and 
provocative field. 

Special features of this second edition include: 

Descriptions of how to do artificial-intelligence work and how to judge 
results. 
Informally defined procedures that provide precision without presuming 
familiarity with a particular programming language. 
Explanations of successful applications programs in commercial use. 
Chapters on logic and learning. 
Many new exercises. 

  

Table of Content: 

THE INTELLIGENT COMPUTER 
The Field and the Book - What Computers Can Do - Criteria for Success 

DESCRIPTION MATCHING AND GOAL REDUCTION 
The Key Role of Representation - Analogy Intelligence Tests - Moving 
Blocks - Problem Solving and Understanding Knowledge 

EXPLOITING NATURAL CONSTRAINTS 
Propagating Symbolic Constraints - Propagating Numeric Constraints - 
Dependency Directed Backtracking 

EXPLORING ALTERNATIVES 
Finding Paths - Finding the Best Path - Dealing With Adversaries 

CONTROL METAPHORS 
Control Choices - Means-Ends Analysis and GPS 

PROBLEM-SOLVING PARADIGMS 
Generate and Test - Rule-Based Systems for Synthesis - Rule-Bases Systems 
for Analysis - Rule-Based Systems for Modeling
Human Thinking 

LOGIC AND THEOREM PROVING 
Rules of Inference - Resolution Proofs - Planning Operator Sequences - 
Proof by Constraint Propagation 

REPRESENTING COMMONSENSE KNOWLEDGE 
Representation - Inheritance, Demons, Defaults and Perspectives - Frames 
and New Stories - Expansion into Primitive Acts -
Abstraction to Summary Units 

LANGUAGE UNDERSTANDING 
From Sentences to World Models - Parsing Sentences - Forming Thematic-
Role Frames - Interpreting Simple Questions and
Commands - Intellectual Partnerships 

IMAGE UNDERSTANDING 
From Images to Object Models - Computing Edge Distance - Computing 
Surface Direction - Interpreting Simple Binary Images -
Robotics 

LEARNING CLASS DESCRIPTIONS FROM SAMPLES 
Induction Heuristics - Induction Procedures - Identification 

LEARNING RULES FROM EXPERIENCE 
Learning Grammar Rules from Sample Sentences - Learning Rulelike 
Principles - Matching is Behind Analogy - Learning from
Functional Definitions - Improving Rules Using Learnable Censors 

EXERCISES 

BIBLIOGRAPHY 
  


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