<p>The first edition of this popular textbook, <b><i>Contemporary Artificial Intelligence</i></b>, provided an accessible and student friendly introduction to AI. This fully revised and expanded update, <b><i>Artificial Intelligence: With an Introduction to Machine Learning, Second Edition, </i></b>
On Machine Intelligence, Second Edition
β Scribed by Donald Michie
- Publisher
- Ellis Horwood Limited
- Year
- 1986
- Tongue
- English
- Leaves
- 276
- Series
- Ellis Horwood Series in Artificial Intelligence
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
Donald Michie was among the pioneers of Bletchley Park from 1942-1945, working with the Colossus series of computers. After a post-war career in biology, for which Oxford University awarded him the D.Sc., he formed the Experimental Programming Unit at Edinburgh in 1965, and conceived and directed the FREDDY robot project, recognised as a world first. He held the chair of Machine Intelligence at Edinburgh from 1967-1985, and is Editor-in-Chief of the acclaimed Machine Intelligence series, as well as co-editing Intelligent Systems (Ellis Horwood, 1983). He is Chief Scientist and Director of Research at the Turing Institute and is a Fellow of the Royal Society of Edinburgh and of the British Computer Society.
This lucid commentary on twenty-five years with machines which learn and plan traces and illuminates the latest progress towards the goal of the intelligent machine. It surveys an integrated sequence of researches undertaken by Professor Michie and his colleagues, while at the same time providing an authoritative introduction to the subject.
This second edition, which has been completely revised and expanded, incorporates much stimulating new material, resulting in a new book rather than a new edition. Half of the present text has been newly written, and fresh introductory notes supplied for each of the book's four main sections. Every chapter is individual and self-sufficient, offering the reader the freedom to select topics to suit his own needs, and helping towards both theoretical and practical approaches to representing cognitive processes in machines.
It is a thought-provoking review which will help satisfy the thirst for information and advice in the fast-growing areas
of artificial intelligence, from the pen of an internationally respected leader in the field. It is fascinating to read, elegant and persuasive in its presentation, and will be widely read not only by scientists and engineers, but by all interested in the role of computers today.
Readership: Scientists, engineers and researchers in artificial intelligence, computing, machine intelligence, robotics, machine learning; knowledge engineering; cognitive science; information science; software engineering; electronics.
β¦ Table of Contents
- Foreword
- Foreword to First Edition
- Preface
- Introduction
- Acknowledgements
Section 1: Computer Game Playing - Introductory note to Section 1
- Trial and error
- Puzzle-learning versus game-learning
- Machines that play and plan
- Evaluative comments in chess
- Computable sub-games of chess
- Computer chess and the humanisation of technology
Section 2: Intelligent Robots - Introductory note to Section 2
- Integrated cognitive systems
- TokyoβEdinburgh dialogue
- Artificial intelligence
- Machine intelligence at Edinburgh
- Machines and the theory of intelligence
- Knowledge engineering
- Machine intelligence as technology
- Steps towards robot intelligence
Section 3: Mechanics of Cognition - Introductory note to Section 3
- Memory mechanisms and machine learning
- Machine models of perceptual and intellectual skills
- High-road and low-road programs
- Measuring the knowledge-content of expert systems
- Automating the synthesis of expertise
Section 4: AI and Society - Introductory note to Section 4
- Computer β servant or master?
- Towards a knowledge accelerator
- Machine intelligence: the first 2400 years
- index
β¦ Subjects
planning, inference, reasoning, logic, programming languages, robotics, history of AI, program synthesis, knowledge engineering, expert systems, reinforcement learning, AI risk, AI effects on society
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