Beyond Artificial Intelligence: Contemplations, Expectations, Applications
Saved in:
| Other Authors: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Heidelberg [u.a.]
Springer
2013
|
| Series: | Topics in Intelligent Engineering and Informatics
4 |
| Subjects: | |
| Online Access: | Inhaltstext Inhaltsverzeichnis |
| Physical Description: | XIII, 238 S. Ill. 235 mm x 155 mm |
| ISBN: | 9783642344213 |
Staff View
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IMAGE 1
CONTENTS
PART I: FUTURE O F ARTIFICIAL INTELLIGENCE 1 ON THE WAY TO INTELLIGENCE
SINGULARITY 3
IVAN M. HAVEL 1.1 WHAT IS SINGULARITY 3
1.2 ARTIFICIAL INTELLIGENCE READY TO START 5
1.3 THE DUAL NATURE OF THE FUTURE TENSE 7
1.4 INTELLIGENCE-WHAT DOES IT ACTUALLY MEAN? 8
1.5 CAN INTELLIGENCE BE MEASURED? 12
1.6 INTELLIGENCE IN MOTION 14
1.7 HOW THE EXPLOSION IS BORN 16
1.8 SPEED OF TIME 20
1.9 I F A MACHINE WERE ABLE TO DESIGN A BETTER MACHINE, WOULD IT DO IT?
21
1.10 WHAT THEN? 23
REFERENCES 26
2 SLIPPAGE IN COGNITION, PERCEPTION, AND ACTION: FROM AESTHETICS TO
ARTIFICIAL INTELLIGENCE 27
WILLIAM W. YORK AND HAMID R. EKBIA 2.1 INTRODUCTION 27
2.2 AESTHETICS: FROM PHILOSOPHY TO AI 2 8
2.2.1 COMPUTATIONAL AESTHETICS AND THE FORMALIST DREAM . . . . 29 2.2.2
A RELATIONAL PERSPECTIVE ON AESTHETICS 30
2.3 COMPUTER MODELS O F ANALOGY-MAKING 31
2.3.1 COPYCAT AND METACAT 32
2.3.2 CONCEPTUAL SLIPPAGE AND THE AESTHETICS OF ANALOGY-MAKING 35
2.4 PERCEPTUAL SLIPPAGE 37
2.4.1 VISUAL ANALOGIES 37
2.4.2 PERCEPTUAL SLIPPAGE AND BLENDING 39
2.4.3 VISUAL ANALOGY IS "SEEING-AS" 41
HTTP://D-NB.INFO/1026468256
IMAGE 2
VIII CONTENTS
2.5 ACTION SLIPS 41
2.5.1 AFFORDANCES AND SLIPPAGE 42
2.5.2 FROM SLIPS AND SLIPPAGE TO AESTHETICS AND AFFECT 4 3
2.6 CONCLUSION 44
REFERENCES 45
3 RATIONALITY {IN |FOR|THROUGH} AI 49
TAREK R. BESOLD 3.1 INTRODUCTION 4 9
3.2 RATIONALITY 50
3.3 A SURVEY: RATIONALITY IN AI 52
3.3.1 RATIONALITY & (NATURAL) INTELLIGENCE 52
3.3.2 WHY SHOULD AI CARE ABOUT RATIONALITY? 53
3.3.3 EARLIER WORK & STATUS QUO 54
3.4 THE GOAL: RATIONALITY FOR AI 55
3.5 AN OUTLOOK: RATIONALITY THROUGH AI 58
3.6 CONCLUSION 59
REFERENCES 6 0
4 USAGE O F "FORMAL RULES" IN HUMAN INTELLIGENCE INVESTIGATIONS . . . .
63 TZU-KENG FU 4.1 INTRODUCTION 63
4.2 FROM FREUD TO BI-LOGIC FRAMEWORK 64
4.2.1 TWO PRINCIPLES IN THE BI-LOGIC FRAMEWORK 64
4.2.2 THE "LOGIC" O F UNCONSCIOUS PROCESSES 65
4.3 THE PHYSICAL FEATURES O F UNCONSCIOUS PROCESSES 6 6
4.3.1 THE CONCEPTIONS O F SPACE-TIME TAKEN IN MATTE BLANCO'S THEORY O F
MIND 6 6
4.3.2 THE DIMENSIONAL TRANSFORMATION BETWEEN THE CONSCIOUS PROCESSES AND
UNCONSCIOUS PROCESSES 67 4.3.3 THE INFINITENESS O F EMOTION IN PSYCHOTIC
68
4.3.4 THE CHARACTERISTICS O F SPACE-TIME IN THE UNCONSCIOUS PROCESSES 68
4.4 THE LOGICAL FEATURES OF UNCONSCIOUS PROCESSES 6 9
4.4.1 THE ABSENCE O F CLASSICAL NEGATION 69
4.4.2 THE PARACONSISTENCY 7 0
4.5 DISCUSSION AND OUTLOOK 71
REFERENCES 72
5 NEW EMERGENCE AS SUPERVENIENCE RELIEVED O F PROBLEMS 75
ELISKA KVETOVA 5.1 INTRODUCTION 7 5
5.2 DEVELOPMENT O F THE RELATIONSHIP O F EMERGENCE AND SUPERVENIENCE 77
5.3 DEVELOPMENT OF THE RELATIONSHIP BETWEEN THE CONCEPTS 78
5.4 EMERGENCE IN ARTIFICIAL INTELLIGENCE 7 9
IMAGE 3
CONTENTS I X
5.5 THE NATURE O F THE RELATIONSHIP BETWEEN SUPERVENIENCE AND
EMERGENCE 80
5.6 NEW EMERGENCE AS CONTINUATION O F SUPERVENIENCE 82
5.7 CONCLUSIONS 83
REFERENCES 84
6 BEYOND KNOWLEDGE SYSTEMS 85
JOZEF KELEMEN 6.1 INTRODUCTION 85
6.2 FROM DATA TO KNOWLEDGE-ROLE O F THE CONTEXT 86
6.3 THE STRUCTURE O F KNOWLEDGE 87
6.4 WHAT IS COMING NOW? 88
6.5 THE ROLE O F THE EMBODIMENT 90
6.6 THROUGH ROBOTIC BODIES TOWARDS THE COMPUTATIONAL WISDOM? 92
REFERENCES 94
PART II: NATURE-INSPIRED MODELS
7 SELFISH GENES AND EVOLUTIONARY COMPUTATION 97
JAN ZELINKA 7.1 INTRODUCTION 97
7.2 EVOLUTION AND SELFISH GENES 98
7.2.1 A GENE DEFINITION 98
7.2.2 SCATTERED GENES 99
7.2.3 SOURCES O F EVOLUTIONS 100
7.2.4 EVOLUTIONARILY STABLE STRATEGY AND EVOLUTIONARILY STABLE
POPULATION 101
7.2.5 SELFISHNESS AND A SELFISH GENE MANIFESTATIONS 102
7.3 EVOLUTIONARY COMPUTATION 103
7.4 SELFISH GENES AND EVOLUTIONARY COMPUTATION 103
7.4.1 STATE O F THE ART 104
7.4.2 SELFISH GENE MANIFESTATIONS IN EXAMPLES AND EXPERIMENTS 104
7.4.3 ADVANTAGES O F SELFISH GENE IN EVOLUTIONARY COMPUTATION 106
7.4.4 METAEVOLUTIONS 108
7.5 SELFISH GENES AND ARTIFICIAL INTELLIGENCE 108
7.6 CONCLUSION 110
REFERENCES 110
8 NONLINEAR TRENDS IN MODERN ARTIFICIAL INTELLIGENCE: A NEW PERSPECTIVE
113
ELENA N. BENDERSKAYA 8.1 INTRODUCTION 113
8.2 MODERN ARTIFICIAL INTELLIGENCE 114
IMAGE 4
X CONTENTS
8.2.1 LIMITATIONS O F BASIC AI APPROACHES 114
8.2.2 EVOLUTION OF FORMAL METHODS: DEALING WITH UNCERTAINTY 115
8.3 NEUROSCIENCE: BRAIN AS CHAOTIC COMPUTER 117
8.4 NOVEL BIO-INSPIRED METHODS AND DYNAMIC NEURAL NETWORKS . . . . 118
8.5 CHAOTIC BIO-INSPIRED SYSTEMS 120
8.6 CHAOTIC COMPUTING 121
8.7 CONCLUSIONS 122
REFERENCES 122
9 MEMBRANE COMPUTING IN ROBOTICS 125
ANA BRANDU§A PAVEL, CRISTIAN LOAN VASILE, AND LOAN DUMITRACHE 9.1
MEMBRANE COMPUTING-AN OVERVIEW 125
9.2 MEMBRANE CONTROLLERS FOR MOBILE ROBOTS 128
9.3 AN OVERVIEW O F THE RESULTS 129
9.4 CONCLUSIONS AND FUTURE DEVELOPMENTS 133
REFERENCES 134
10 IMPLEMENTING ENZYMATIC NUMERICAL P SYSTEMS FOR A I APPLICATIONS BY
MEANS O F GRAPHIC PROCESSING UNITS 137
MANUEL GARCIA-QUISMONDO, LUIS F. MACFAS-RAMOS, AND MARIO J.
PEREZ-JIMENEZ 10.1 INTRODUCTION 137
10.2 PRELIMINARIES 138
10.2.1 P SYSTEMS 138
10.2.2 NUMERICAL P SYSTEMS 140
10.3 ENZYMATIC NUMERICAL P SYSTEMS 142
10.3.1 DESCRIPTION O F ENZYMATIC NUMERICAL P SYSTEMS 142
10.3.2 ENPSS AND ARTIFICIAL INTELLIGENCE 143
10.3.3 SIMULATION OF ENPSS 143
10.4 THE COMPUTE UNIFIED DEVICE ARCHITECTURE (CUDA) STANDARD FOR GPU
COMPUTING 144
10.4.1 OUTLINE O F THE CUDA PROGRAMMING MODEL 144
10.4.2 THE C U D A - C PROGRAMMING LANGUAGE 144
10.5 A GPU-BASED SIMULATOR FOR ENZYMATIC NUMERICAL P SYSTEMS 146
10.5.1 DATA REPRESENTATION 146
10.5.2 REPARTITION COEFFICIENTS NORMALIZATION 147
10.5.3 PROGRAM CHECKING 147
10.5.4 CALCULATION OF PRODUCTION FUNCTIONS 148
10.5.5 VARIABLE CLEARING 151
10.5.6 REPARTITION PROTOCOL APPLICATION 152
10.5.7 EXECUTION O F A SIMULATION STEP 153
10.5.8 REMARKS ON THE SIMULATOR 154
IMAGE 5
CONTENTS X I
10.6 SIMULATOR PERFORMANCE 154
10.6.1 SIMULATOR WORKFLOW 154
10.6.2 PERFORMANCE COMPARISON 154
10.7 CONCLUSIONS 156
REFERENCES 157
11 HOW TO DESIGN AN AUTONOMOUS CREATURE BASED ON ORIGINAL ARTIFICIAL
LIFE APPROACHES 161
PAVEL NAHODIL AND JAROSLAV VFTKU 11.1 INTRODUCTION - HISTORY O F
ARTIFICIAL LIFE RESEARCH 161
11.2 STATE-OF-THE-ART - COMPARISON TO SIMILAR ARCHITECTURES 163 11.2.1
INTEGRATING NEURAL NETWORKS AND KNOWLEDGE-BASED SYSTEMS FOR INTELLIGENT
ROBOTIC CONTROL 163
11.2.2 REINFORCEMENT-LEARNING TELEO-OPERATORS 164
11.3 ARCHITECTURE WITH ELEMENTS O F HIERARCHY, ABSTRACTION,
REINFORCEMENTS AND MOTIVATIONS 165
11.3.1 MAIN IDEAS O F THE HARM APPROACH 166
11.3.2 SAMPLE EXPERIMENT: THE TREASURE PROBLEM 168
11.4 PROPOSED AUTONOMOUS CREATURE 169
11.4.1 BRIEF DESCRIPTION OF DESIGNED ARCHITECTURE 169
11.4.2 AUGMENTING ORIGINAL HIERARCHICAL LEARNING SYSTEM . . . 170 11.4.3
INTENTIONAL STATE SPACE 171
11.4.4 DELIBERATIVE ACTION SELECTION - PLANNING 171
11.4.5 ARTIFICIAL NEURAL NETWORK - LEARNING THE REFLEXIVE BEHAVIOR 172
11.5 SELECTED EXPERIMENTS 173
11.5.1 TWO.ATTRACTORS IN COMPLEX ENVIRONMENT - HIERARCHY CREATION 174
11.5.2 P A R T I - C R E A T I O N O F HIERARCHY BASED ON INTENTIONS . .
. 175 11.5.3 PART 2 - PLANNING OVER THE HIERARCHY OF DECISION SPACES 176
11.6 CONCLUSION 178
REFERENCES 179
PART III: WHEN ARTIFICIAL BECOMES NATURAL
12 A VIEW ON CO-EXISTENCE O F VARIOUS ENTITIES IN INTELLIGENT
ENVIRONMENTS . . . .- 183
PETER MIKULECKY AND PETR TUCNIK 12.1 INTRODUCTION 183
12.2 RELATED WORKS 185
12.3 CO-EXISTENTIAL VIEW 188
12.4 PERCEIVING USERS AND ENVIRONMENT 189
IMAGE 6
X I I
CONTENTS
12.5 SIGNIFICANCE O F ROLES 192
12.6 CONCLUSIONS 194
REFERENCES 194
13 MULTI-AGENT SYSTEMS IN INDUSTRY: CURRENT TRENDS & FUTURE CHALLENGES
197
PAULO LEITAO 13.1 INTRODUCTION 197
13.2 ARTIFICIAL INTELLIGENCE AND MULTI-AGENT SYSTEMS 198
13.3 APPLICATIONS O F MAS IN INDUSTRY 198
13.4 CURRENT TRENDS AND FUTURE CHALLENGES 200
13.5 CONCLUSIONS 200
REFERENCES 201
14 VOICE CONSERVATION: TOWARDS CREATING A SPEECH-AID SYSTEM FOR TOTAL
LARYNGECTOMEES 203
ZDENEK HANZLICEK, JAN ROMPORTL, AND JINDRICH MATOUSEK 14.1 INTRODUCTION
203
14.2 PRACTICAL ASPECTS 205
14.3 VOICE CONSERVATION 207
14.4 PROPOSED SYSTEM LAYOUT 208
14.5 SPEECH SYNTHESIS 209
14.6 PRELIMINARY EXPERIMENTS 210
14.7 CONCLUSION 211
REFERENCES 212
15 EXTENDED MIND: IS THERE ANYTHING AT ALL TO BE EXTERNALISED? 213 EVA
ZACKOVA AND JAN ROMPORTL 15.1 INTRODUCTION 213
15.2 EXTENDED MIND CONCEPTION 214
15.3 EXPRESS YOURSELF-EXTED YOURSELF: LANGUAGE AS A MIND-TRANSFORMER 214
15.4 CRITERIONS O F EXTERNAL COGNITIVE PROCESS 217
15.5 HARD-WIRED SYSTEM CRITERION 218
15.6 SPEECH PROSTHETICS AS A REAL-LIFE APPLICATION OF EXTENDED MIND 218
15.7 INTERNAL AND EXTERNAL 219
REFERENCES 220
16 EMBODIED AGENT OR MASTER O F PUPPETS: HUMAN IN RELATION WITH HIS
AVATAR 223
MATEUSZ WOZNIAK 16.1 INTRODUCTION 223
16.2 TREATING ARTIFICIAL AS REAL 224
16.3 AVATAR-VIRTUAL BODY 225
16.4 BODY REPRESENTATIONS 226
IMAGE 7
CONTENTS XIII
16.5 RESEARCH 228
16.5.1 PURPOSE AND METHODS 228
16.5.2 RESULTS 230
16.6 DISCUSSION AND CONCLUSIONS 233
REFERENCES 234
INDEX 237 |
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| title | Beyond Artificial Intelligence Contemplations, Expectations, Applications |
| title_auth | Beyond Artificial Intelligence Contemplations, Expectations, Applications |
| title_exact_search | Beyond Artificial Intelligence Contemplations, Expectations, Applications |
| title_full | Beyond Artificial Intelligence Contemplations, Expectations, Applications Jozef Keleman ... (eds.) |
| title_fullStr | Beyond Artificial Intelligence Contemplations, Expectations, Applications Jozef Keleman ... (eds.) |
| title_full_unstemmed | Beyond Artificial Intelligence Contemplations, Expectations, Applications Jozef Keleman ... (eds.) |
| title_short | Beyond Artificial Intelligence |
| title_sort | beyond artificial intelligence contemplations expectations applications |
| title_sub | Contemplations, Expectations, Applications |
| topic | Künstliche Intelligenz (DE-588)4033447-8 gnd |
| topic_facet | Künstliche Intelligenz Konferenzschrift 2011 Pilsen |
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