This book is based upon course material used by one of the authors on anintroductory course in artificial intelligence (AI) at the University of York. The course was taught to MSc conversion course students who had little technical background and only basic level mathematics. Available text-books in AI either assumed too much technical knowledge or provided a very limited coverage ofthe subject. This book is an attempt to fill this gap. Its aim is to provide accessible coverage of the key areas of AI, in such a way that it will be understandable to those with only a basic knowledge of mathematics.
The book takes a pragmatic approach to AI, looking at how AI techniques areapplied to various application areas. It is structured in two main sections. The first part introduces the key techniques used in AI in the areas of knowledge rep resentation, search, reasoning and learning. The second part covers application areas including game playing, expert systems, natural language understanding, vision, robotics, agents and modelling cognition. The book concludes with abrief consideration of some of the philosophical and social issues relating to the subject.
It does not claim to be comprehensive: there are many books on the marketwhich give more detailed coverage. Instead it is designed to be used to support a one-semester introductory module in AI (assuming a 12 week module with alecture and practical session). Depending on the emphasis of the module, possible course structures include spending one week on each of the 12 main chapters or spending more time on techniques and selecting a subset of the application areas to consider.
Table of Contents:
Introduction
What is artificial intelligence?
History of artificial intelligence
The future for AI
1. Knowledge in AI
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
2. Reasoning
Overview
What is reasoning?
Forward and backward reasoning
Reasoning with uncertainty
Summary
Exercises
Recommended further reading
3. Search
Introduction
Exhaustive search and simple pruning
Heuristic search
Knowledge-rich search
Summary
Exercises
Recommended further reading
4.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
5.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
6.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
Hybrid expert systems
Summary
Exercises
Recommended further reading
7.Natural language understanding
Overview
What is natural language understanding?
Why do we need natural language understanding?
Why is natural language understanding difficult?
Anearly 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
8.Computer vision
Overview
Introduction
Digitization and signal processing
Edge detection
Region detection
Reconstructing objects
Identifying objects
Multiple images
Summary
Exercises
Recommended further reading
9.Planning and robotics
Overview
Introduction
Global planning
Local planning
Limbs, legs and eyes
Practical robotics
Summary
Exercises
Recommended further reading
Agents
verview
Software agents
Co-operating agents and distributed AI
Summary
Exercises
Recommended further reading
11.Models of the mind
Overview
Introduction
What is the human mind?
Production system models
Connectionist models of cognition
Summary
Exercises
Recommended further reading
Notes
12.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
Author: Janet Finlay & Alan Dix
Support the authors by buying their original books, so they can write even more books that you like
Loppat!
