An authoritative and accessible one-stop resource, An Introduction to Artificial Intelligence presents the first full examination of AI. Designed to provide an understanding of the foundations of artificial intelligence, it examines the central computational techniques employed by AI, including knowledge representation, search, reasoning, and learning, as well as the principal application domains of expert systems, natural language, vision, robotics, software agents and cognitive modeling. Many of the major philosophical and ethical issues of AI are also introduced.
Throughout the volume, the authors provide detailed, well-illustrated treatments of each topic with abundant examples and exercises. The authors bring this exciting field to life by presenting a substantial and robust introduction to artificial intelligence in a clear and concise coursebook form. This book stands as a core text for all computer scientists approaching AI for the first time.
Overview
Introduction
Representing Knowledge
Metrics for Assessing Knowledge Representation Schemes
Logic Representations
Procedural Representation
Network Representations
Structured Representations
General Knowledge
The Frame Problem
Knowledge Elicitation
Summary
Exercises
Recommended Further Reading
REASONING
Overview
What is Reasoning?
Forward and Backward Reasoning
Reasoning with Uncertainty
Summary
Exercises
Recommended Further Reading
SEARCH
Introduction
Exhaustive Search and Simple Pruning
Heuristic Search
Knowledge-Rich Search
Summary
Exercises
Recommended Further Reading
MACHINE LEARNING
Overview
Why Do We Want Machine Learning?
How Machines Learn
Deductive Learning
Inductive Learning
Explanation-Based Learning
Example: Query-by-Browsing
Summary
Recommended Further Reading
GAME PLAYING
Overview
Introduction
Characteristics of Game Playing
Standard Games
Non-Zero-Sum Games and Simultaneous Play
The Adversary is Life!
Probability
Summary
Exercises
Recommended Further Reading
EXPERT SYSTEMS
Overview
What Are Expert Systems?
Uses of Expert Systems
Architecture of an Expert System
Examples of Four Expert Systems
Building an Expert System
Limitations of Expert Systems
Summary
Exercises
Recommended Further Reading
NATURAL LANGUAGE UNDERSTANDING
Overview
What is Natural Language Understanding?
Why Do We Need Natural Language Understanding?
Why Is Natural Language Understanding Difficult?
An Early Attempt at Natural Language Understanding: SHRDLU
How Does Natural Language Understanding Work?
Syntactic Analysis
Semantic Analysis
Pragmatic Analysis
Summary
Exercises
Recommended Further Reading
Solution to SHRDLU Problem
COMPUTER VISION
Overview
Introduction
Digitization and Signal Processing
Edge Detection
Region Detection
Reconstructing Objects
Identifying Objects
Multiple Images
Summary
Exercises
Recommended Further Reading
PLANNING AND ROBOTICS
Overview
Introduction
Global Planning
Local Planning
Limbs, Legs, and Eyes
Practical Robotics
Summary
Exercises
Recommended Further Reading
AGENTS
Overview
Software Agents
Co-operating Agents and Distributed AI
Summary
Exercises
Recommended Further Reading
MODELS OF THE MIND
Overview
Introduction
What is the Human Mind?
Production System Models
Connectionist Models of Cognition
Summary
Exercises
Recommended Further Reading
Notes
EPILOGUE: PHILOSOPHICAL AND SOCIOLOGICAL ISSUES
Overview
Intelligent Machines or Engineering Tools?
What Is Intelligence?
Computational Argument vs. Searle's Chinese Room
Who Is Responsible?
Morals and Emotions
Social Implications
Summary
Recommended Further Reading
