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How to Grow a Robot: Developing Human-Friendly, Social AI [Kõva köide]

(Aberystwyth University)
  • Formaat: Hardback, 384 pages, kõrgus x laius x paksus: 229x152x25 mm, 32 b&w illus.; 64 Illustrations
  • Sari: The MIT Press
  • Ilmumisaeg: 28-Apr-2020
  • Kirjastus: MIT Press
  • ISBN-10: 0262043734
  • ISBN-13: 9780262043731
Teised raamatud teemal:
  • Formaat: Hardback, 384 pages, kõrgus x laius x paksus: 229x152x25 mm, 32 b&w illus.; 64 Illustrations
  • Sari: The MIT Press
  • Ilmumisaeg: 28-Apr-2020
  • Kirjastus: MIT Press
  • ISBN-10: 0262043734
  • ISBN-13: 9780262043731
Teised raamatud teemal:
"Mark Lee considers that the current gains in machine learning and deep learning will not produce robots that can interact effectively with humans. The book then explores how robots can become more human-like, more general-purpose, and more social. The book introduces us to the core ideas in Developmental Robotics - showing how this new approach can "grow" robots through (their own) experience rather than building them from design. Original aspects include demonstrating that social robots must be embodied, that embodiment will be necessary for general artificial intelligence, and that threats from advanced technology are not inevitable but avoidable by involving human, social, and ethical issues. The material covers a wide scope; from simple robots to advanced AI. This gives an overview of this area and an appreciation of the main advances, problems, and issues. The scope if the readership is intended to be wide: aimed at a general, educated but not specialist audience. For this reason, an engineering viewpoint is adopted; technical details and philosophical aspects are minimized, thus promoting a practical perspective. The aim is to present the fundamental ideas behind AI and robotics in a clear, accessible form, appealing to common sense, so as to encourage the general reader to build their own informed assessment of these technologies. The hope is to reach a wide public readership - reaching anyone who wishes to know what robotics is about, where it is going, and what its limitations are"--

How to develop robots that will be more like humans and less like computers, more social than machine-like, and more playful and less programmed.

Most robots are not very friendly. They vacuum the rug, mow the lawn, dispose of bombs, even perform surgery—but they aren't good conversationalists. It's difficult to make eye contact. If the future promises more human-robot collaboration in both work and play, wouldn't it be better if the robots were less mechanical and more social? In How to Grow a Robot, Mark Lee explores how robots can be more human-like, friendly, and engaging.

Developments in artificial intelligence—notably Deep Learning—are widely seen as the foundation on which our robot future will be built. These advances have already brought us self-driving cars and chess match–winning algorithms. But, Lee writes, we need robots that are perceptive, animated, and responsive—more like humans and less like computers, more social than machine-like, and more playful and less programmed. The way to achieve this, he argues, is to “grow” a robot so that it learns from experience—just as infants do.

After describing “what's wrong with artificial intelligence” (one key shortcoming: it's not embodied), Lee presents a different approach to building human-like robots: developmental robotics, inspired by developmental psychology and its accounts of early infant behavior. He describes his own experiments with the iCub humanoid robot and its development from newborn helplessness to ability levels equal to a nine-month-old, explaining how the iCub learns from its own experiences. AI robots are designed to know humans as objects; developmental robots will learn empathy. Developmental robots, with an internal model of “self,” will be better interactive partners with humans. That is the kind of future technology we should work toward.



How to develop robots that will be more like humans and less like computers, more social than machine-like, and more playful and less programmed.
Preface xiii
Acknowledgments xv
What's Wrong With Artificial Intelligence? 1(2)
1 The Nature of the Problem
3(16)
Acting and Thinking
4(2)
The Social Robot
6(1)
The Role of Artificial Intelligence
7(1)
Intelligence in General
7(2)
Brains Need Bodies
9(1)
The Structure and Theme of This Book
9(7)
Coping with the Pace of Change
16(2)
A Note on Jargon
18(1)
2 Commercial Robots
19(16)
Domestic Robots and Service Robots
20(2)
Field Robotics
22(1)
Robotic Road Vehicles
23(3)
Medical Robots
26(1)
Swarm Robotics
27(2)
Entertainment Robots
29(1)
Companion Robots
30(1)
Humanlike Robots?
31(1)
Observations
32(3)
3 From Research Bench to Market
35(20)
Bin Picking
38(2)
Biorobotics
40(1)
Care and Assistive Robots
40(1)
Affective Computing
41(1)
Humanoid Robots
42(4)
Why Has Industrial Robotics Been So Successful?
46(4)
The Current State of Robotics
50(3)
Observations
53(2)
4 A Tale of Brute Force
55(12)
Searching through the Options
56(2)
The World Chess Champion Is a Computer---So What?
58(4)
Computer "Thinking"
62(1)
The Outcome
63(2)
Observations
65(2)
5 Knowledge Versus Power
67(14)
How Can Knowledge Be Stored for Utilization?
70(2)
Common Sense Knowledge
72(2)
Search Is a Standard Technique
74(1)
Symbols and Numbers
75(1)
Learning to Improve
75(2)
Feature Engineering
77(1)
Observations
78(3)
6 A Little Vision and a Major Breakthrough
81(14)
The End of Feature Engineering
86(5)
What Happened?
91(1)
Observations
92(3)
7 The Rise of the Learning Machines
95(16)
The Evolution of Machine Learning
96(1)
Data Mining in Supermarkets
97(3)
Learning Algorithms That Learn Algorithms
100(1)
Discovering Patterns
101(1)
Big Data
102(2)
Statistics Is Important, but Misunderstood
104(1)
The Revolution Continues---with Deep Zero
105(4)
Observations
109(2)
8 Deep Thought and Other Oracles
111(14)
AI Is a Highly Focused Business
112(1)
Task-Based AI
113(1)
Machine Oracles
114(4)
Knowledge Engineering
118(3)
Social Conversation
121(3)
Observations
124(1)
9 Building Giant Brains
125(20)
Brain-Building Projects
126(2)
Whole Brain Emulation (WBE)
128(2)
The Brain Is a Machine---So What?
130(3)
Basic Artificial Neural Networks (ANNs)
133(1)
Different Approaches: AI and Brain Science
134(3)
More Advanced Networks
137(1)
Predictive Coding and Autoencoders
138(1)
Issues with ANNs
139(2)
Simulation Problems for Robots
141(2)
Observations
143(2)
10 Bolting it all Together
145(22)
The Complexity of Modular Interactions
146(3)
How Can Computers Represent What They Know and Experience?
149(2)
The Limitations of Task-Based AI
151(1)
General AI
151(1)
Master Algorithms
152(2)
Biological Comparisons
154(1)
Superintelligence (SI)
155(3)
Integrating Deep Artificial Neural Networks (ANNs)
158(2)
Observations for Part I
160(7)
II ROBOTS THAT GROW AND DEVELOP
167(62)
11 Groundwork---Synthesis, Grounding, and Authenticity
169(12)
The Classical Cybernetics Movement
171(3)
Modern Cybernetics
174(2)
Symbol Grounding
176(1)
The New Robotics
177(2)
Observations
179(2)
12 The Developmental Approach---Grow Your Own Robot
181(26)
The Role of Ontogeny: Growing Robots
184(1)
Sequences, Stages, and Timelines
185(3)
Constraints on Development
188(3)
Start Small and Start Early
191(2)
The Importance of Anatomy
193(2)
The Amazing Complexity of the Human Body
195(2)
Autonomy and Motivation
197(1)
Play---Exploration and Discovery without Goals
198(3)
An Architecture for Growth
201(5)
Observations
206(1)
13 Developmental Growth in the Icub Humanoid Robot
207(22)
iCub---A Humanoid Robot for Research
208(2)
Managing the Constraints of Immaturity
210(1)
Vision, Gazing, and Fixations
211(2)
Motor and Visual Spaces
213(2)
Object Perception
215(1)
Experiment 1---Longitudinal Development
215(2)
Experiment 2---The Generation of Play Behavior
217(4)
How Does It Work?
221(8)
III WHERE DO WE GO FROM HERE?
229(84)
14 How Developmental Robots Will Develop
231(22)
How Developmental Robots Behave
232(5)
Taught, not Programmed
237(2)
Knowing Oneself and Other Agents
239(2)
Self-Awareness Is Common in Animals
241(1)
Robot Selyes
242(2)
Consciousness
244(2)
Communication
246(1)
Developmental Characteristics
247(1)
Will All This Happen?
248(2)
We Must Get Out More ...
250(1)
Observations
251(2)
15 How Ai and Ai-Robots are Developing
253(14)
Task-Based AI
253(2)
Human-Level AI (HLAI)
255(2)
Deep AI
257(2)
Robot Developments
259(1)
Social Robots
260(2)
Artificial Human Intelligence (AHI)
262(2)
Observations
264(3)
16 Understanding Future Technology
267(26)
Rapid Growth---It's Not Really Exponential
268(2)
Growth Patterns in the Twenty-First Century---So Far
270(2)
Artificial General Intelligence (AGI)
272(1)
Deep Networks, Learning, and Autonomous Learning
273(1)
Are There Any Dead Certainties?
274(4)
Trust, Validation, and Safety
278(1)
The Product-Centred Viewpoint
279(5)
The Crucial Role of Humans
284(2)
The Ethical Viewpoint
286(2)
Lessons from Opaque and Unregulated Markets
288(2)
Observations
290(3)
17 Futurology and Science Fiction
293(20)
Are We Smart Enough to Know How Smart Animals Are?
294(1)
What Kind of World Do We Live In?
295(1)
Futurology, Expert Opinion, and Meta-opinions
296(4)
Threats on the Horizon?
300(1)
Superintelligence and the Singularity
300(2)
Transhumanism---Downloading the Brain
302(1)
Imminent Threats
303(3)
Toward Dystopia?
306(3)
It's Not All Doom and Gloom!
309(1)
Threats in Perspective
310(1)
Final Remarks
310(3)
Appendix: Principles for the Developmental Approach 313(6)
Notes 319(20)
Bibliography 339(18)
Index 357