Artificial Psychology - The Quest for What It Means to Be Human - J. Friedenberg (Psych. Press, 2008) WW

313 Pages·2008·8.66 MB·English

ARTIFICIAL
PSYCHOLOGY

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Psychology Press
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iii

CONTENTS

Figures
v

Tables
ix

Preface
xi

About the Author
xv

Chapter 1
Introduction
1

Chapter 2
Brain and Mind
17

Chapter 3
Perception and Action
37

Chapter 4
Learning and Memory
55

Chapter 5
Th inking
73

Chapter 6
Language
91

Chapter 7
Intelligence
109

Chapter 8
Creativity
127

Chapter 9
Free Will and Decision Making
147

Chapter 10
Consciousness
163

Chapter 11
Motivation and Emotion
179

Chapter 12
Biology
201

Chapter 13
Social Behavior
217

Chapter 14
Conclusion
235

iv • Contents

Glossary
255

References
271

Name Index
285

Subject Index
291

v

FIGURES

1.1
Th e android “Jules” by Hanson Robotics shows off at NextFest 2006.
Androids look and act like people but are not considered human.
4
1.2
Elektro and Sparko, mechanical man and dog, get together before going out
to the Westinghouse Exhibit at the 1939–40 World’s Fair.
8
1.3
Natural and artifi cial approaches to engineering a capacity like fl ying.
12
2.1
Th e anatomy of a neuron.
18
2.2
A mid-sagittal section of the human brain.
19
2.3
Is the mind the same as the brain?
20
2.4
Parallel and serial information-processing architectures. Boxes indicate
modules or places where computations take place. Arrows indicate the fl ow
of information as inputs and outputs between modules.
25
2.5
Th e basic functional hardware of most modern computers consists of
memory, input-output devices, and a central processing unit that share
a common communication bus. Th is is also known as a Von Neumann
architecture.
28
2.6
An example of a three-layer artifi cial neural network.
30
3.1
NASA and DARPA have developed Robonaut for work on the International
Space Station. Robonaut has a dexterous fi ve-fi ngered hand that can grasp
and manipulate a wide variety of tools.
45
3.2
General schematic architecture for an agent.
47
3.3
Cog and his designer Rodney Brooks play with a slinky. Cog was developed
at the MIT Artifi cial Intelligence Laboratory and can use haptic feedback to
adjust its actions and is also capable of copying human behavior.
51
3.4
Honda’s ASIMO robot shakes hands. It can also walk on level surfaces and
up and down stairs.
54
4.1
An associative network like this can be classically conditioned. It can learn
to make associations between two stimuli that co-occur frequently.
57

vi • Figures

4.2
A model showing the diff erent types of human memory and memory
processes.
65
4.3
A semantic network is used to represent and organize information about
facts.
68
5.1
Th e Turing Test. A computer program has not yet been devised that can
fool a human judge.
75
5.2
Th e hypothetical Chinese Room scenario. Is rule-following enough to allow
for understanding?
78
5.3
Human thoughts are intentional. Th ey are directed toward something in
the world. One aspect of intentionality is an appropriate causal relation.
Th inking about a house might trigger childhood memories that one could
then talk about.
84
6.1
People eff ortlessly use language to communicate complex ideas to one
another. Language is thus the ideal medium for human-machine interaction.
92
6.2
Two of Luc Steel’s robotic agents focus on the same object and use a word to
express it. Th ey are able to spontaneously develop a language and use it to
create shared meaning.
95
6.3
A sentence tree diagram depicts the diff erent parts of an utterance.
Recovery of this type of structure is necessary in order to understand speech. 100
6.4
Th e organization of the Lotus Conversational Interface (LCI) program.
Developed at IBM Research, it is capable of carrying on limited spoken
dialogues with human users.
107
7.1
Examples of questions that might be found on the verbal section of the
Wechsler Adult Intelligence Scale (WAIS).
112
7.2
Depiction of a block world. Instructions given to a program like SHRDLU
are interpreted and used to perform actions such as picking up one shape
and placing it on top of another.
116
7.3
A game tree for tic-tac-toe. Each branch in the tree represents a possible
move, each node the result of a move.
119
7.4
Th e architecture of an expert system (ES). An ES can be used to solve
complex problems such as medical diagnoses that require specialized
knowledge.
121
7.5
Shakey was one of the fi rst robots to use planning to move about simplifi ed
environments.
123
7.6
A schematic representation of human cortical organization. It is
characterized by increasing levels of abstraction that allow for recognition,
expectation, and cross-modal comparison.
125
8.1
A spatial insight problem illustrating convergent thinking. Can you connect
all nine dots using just four straight lines?
133

Figures • vii

8.2
A painting by AARON.
139
8.3
Th e BRUTUS system architecture. When given appropriate information,
BRUTUS can create complex stories.
141
9.1
Cortical regions underlying voluntary motor action.
149
9.2
A decision tree depicting how a college department might go about hiring a
new faculty member.
153
10.1
Pentti Haikonen’s cognitive model of consciousness based on human neural
processing.
170
10.2
A model showing Baar’s Global Workspace Th eory. It serves as the
inspiration for Stan Franklin’s Intelligent Distribution Agent.
172
11.1
Psychologist Abraham Maslow formulated a hierarchy of human needs. In
his model, we work to satisfy lower-level needs fi rst. Once these are taken
care of, we then turn our attention to satisfying higher-level needs.
181
11.2
A thermostat is a very simple device that uses negative feedback to maintain
fl uctuations about a constant state. Our bodies also employ such principles.
183
11.3
Fear pathways. Th e “low” road through the amygdala mediates fast
emotional responding. Th e “high” road through the cortex allows for slower
thoughtful consideration.
190
11.4
Th e diff erent human brain areas involved in emotional responding.
192
11.5
Th e CogAff architecture models many of the steps involved in emotional
processing.
195
11.6
Kismet expresses surprise as Cynthia Breazeal shows it a children’s toy.
Kismet displays facial emotions in response to human interaction and built-
in drive systems. It can display interest, surprise, happiness, disgust, anger,
sadness, fear, fatigue, and calm.
197
12.1
Creatures from Conway’s Game of Life. Th ese dynamic two-dimensional
“life-forms” emerged spontaneously in a system governed by very

simple rules.
205
12.2
Crossover of binary code is a type of “mating” whereby genetic material
from two sources, such as a male and female, are swapped. Th e result are
“off spring” with a new combination of instructions, similar to, but not
identical with, their “parents.”
207
12.3
Researchers in Th e Golem Project at Brandeis University created robots that
locomote under their own power. Th e robots were assembled from basic
parts that included rigid and moveable rods. Th e results were not designed a
priori, but emerged from evolutionary principles.
209
12.4
A schematic of the AbioCor™ Implantable Replacement Heart. An external
battery wirelessly transmits power to an internal rechargeable battery. Th e
controller unit senses and controls pumping speed.
213

viii • Figures

12.5
“Chew-Chew” the gastrobot, developed by Th e Gastrobotics Group at
Th e University of South Florida. Chew-Chew obtains all its energy needs
through sugar cubes placed into its “mouth.” Th e goal is to develop robots
that are energy self-suffi cient in natural outdoor environments.
215
13.1
A bidding process of the sort used in multi-agent systems. Th ese
protocols allow the best agent to get the job and mimic the kinds of group
interactions we see in human societies.
220
13.2
A humanoid entry in the 2006 RoboCup contest. Will robots beat humans
in the World Cup soccer championship by 2050?
222
13.3
Boilerplate with Pancho Villa, 1916. Did Boilerplate really exist?
225
13.4
Th e “uncanny valley.” When robots look humanlike but are clearly
discernible as non-human, they produce a negative emotional response.
226
13.5
ISAC’s multi-agent architecture. Designed by researchers at Vanderbilt
University, ISAC can interpret and respond to people’s intentions.
229
14.1
Historically, computing power has shown tremendously fast increases. By
current estimates, we will be able to artifi cially reproduce the computing
power of the human brain by about 2020.
243
14.2
An artifi cial geisha girl performs a dance routine. Robotic presence in our
everyday days is likely to increase in the future. Robots may perform many
of the functions we now only perceive humans as capable of doing.
247
14.3
Hans Moravec suggests we may ultimately be able to transfer our
consciousness to machine receptacles and so attain immortality. Is this
possible?
249

ix

TABLES

1.1
Diff erent defi nitions of personhood according to Foerst (2004).
3
2.1
Major parts of the human brain and their function.
19
5.1
Diff erent features of computable and uncomputable processes.
90
6.1
Selected dialogue act tags in the DAMSL program. Forward-looking
functions identify the type of statements made by a conversational partner.
Backward-looking functions identify the relationship of an utterance to
previous utterances by the other speaker.
106
9.1
Key stages in the evolution of freedom, according to Dennett (2003).
151
9.2
Calculating a weighted average is one way to determine which of four
schools to attend. It is an example of outstanding candidate choice because
the school with the highest score is the one that is picked.
156