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• Introduction xi Acknowledgements xiii
• Chapter 1. Consciousness: an Ancient and Current Topic of Study 1 1.1. Multidisciplinarity of the subject 1 1.2. Terminological outlook 2 1.3. Theological point of view 4 1.4. Notion of belief and autonomy 5 1.5. Scientific schools of thought 6 1.6. The question of experience 7
• Chapter 2. Self-motivation on a Daily Basis 9 2.1. In news blogs 9 2.2. Marketing 9 2.3. Appearance 10 2.4. Mystical experiences 11 2.5. Infantheism 11 2.6. Addiction 11
• Chapter 3. The Notion of Need 15 3.1. Hierarchy of needs 15 3.1.1. Level-1 needs 16 3.1.2. Level-3 needs 17 3.2. The satiation cycle 18
• Chapter 4. The Models of Social Organization 21 4.1. The entrepreneurial model 21 4.2. Motivational and ethical states 23
• Chapter 5. Self Theories 29
• Chapter 6. Theories of Motivation in Psychology 33 6.1. Behavior and cognition 33 6.2. Theory of self-efficacy 34 6.3. Theory of self-determination 38 6.4. Theory of control 39 6.5. Attribution theory 39 6.6. Standards and self-regulation 42 6.7. Deviance and pathology 47 6.8. Temporal Motivation Theory 48 6.9. Effect of objectives 49 6.10. Context of distance learning 49 6.11. Maintenance model 49 6.12. Effect of narrative 49 6.13. Effect of eviction 50 6.14. Effect of the teacher student relationship 50 6.15. Model of persistence and change 50 6.16. Effect of the man machine relationship 51
• Chapter 7. Theories of Motivation in Neurosciences 53 7.1. Academic literature on the subject 53 7.2. Psychology and Neurosciences 53 7.3. Neurophysiological theory 54 7.4. Relationship between the motivational system and the emotions 56 7.5. Relationship between the motivational system and language 58 7.6. Relationship between the motivational system and need 59
• Chapter 8. Language Modeling 61 8.1. Issues surrounding language 61 8.2. Interaction and language 61 8.3. Development and language 62 8.4. Schools of thought in linguistic sciences 62 8.5. Semantics and combination 68 8.6. Functional grammar 68 8.7. Meaning-Text Theory 69 8.8. Generative lexicon 70 8.9. Theory of synergetic linguistics 70 8.10. Integrative approach to language processing 71 8.11. New spaces for date production 73 8.12. Notion of ontology 75 8.13. Knowledge representation 76
• Chapter 9. Computational Modeling of Motivation 81 9.1. Notion of a computational model 81 9.2. Multi-agent systems 81 9.3. Artificial self-organization 85 9.4. Artificial neural networks 87 9.5. Free will theorem 88 9.6. The probabilistic utility model 89 9.7. The autoepistemic model 91
• Chapter 10. Hypothesis and Control of Cognitive Self-Motivation 93 10.1. Social groups 93 10.2. Innate self-motivation 95 10.3. Mass communication 96 10.4. The Cost Benefit ratio 97 10.5. Social representation 98 10.6. The relational environment 99 10.7. Perception 100 10.8. Identity 100 10.9. Social environment 101 10.10. Historical antecedence 102 10.11. Ethics 102
• Chapter 11. A Model of Self-Motivation which Associates Language and Physiology 105 11.1. A new model 105 11.2. Architecture of a self-motivation subsystem 106 11.3. Level of certainty 108 11.4. Need for self-motivation 108 11.5. Notion of motive 109 11.6. Age and location 113 11.7. Uniqueness 113 11.8. Effect of spontaneity 114 11.9. Effect of dependence 114 11.10. Effect of emulation 115 11.11. Transition of belief 115 11.12. Effect of individualism 117 11.13. Modeling of the groups of beliefs 117
• Chapter 12. Impact of Self-Motivation on Written Information 123 12.1. Platform for production and consultation of texts 123 12.2. Informational measure of the motives of self-motivation 124 12.2.1. Intra-phrastic extraction 125 12.2.2. Inter-phrastic extraction 126 12.2.3. Meta-phrastic extraction 128 12.3. The information market 129 12.4. Types of data 130 12.5. The outlines of text mining 133 12.6. Software economy 139 12.7. Standards and metadata 139 12.8. Open-ended questions and challenges for text-mining methods 140 12.9. Notion of lexical noise 141 12.10. Web mining 143 12.11. Mining approach 145
• Chapter 13. Non-Transversal Text Mining Techniques 147 13.1. Constructivist activity 147 13.2. Typicality associated with the data 148 13.3. Specific character of text mining 148 13.4. Supervised, unsupervised and semi-supervised techniques 149 13.5. Quality of a model 149 13.6. The scenario 149 13.7. Representation of a datum 150 13.8. Standardization 151 13.9. Morphological preprocessing 152 13.10. Selection and weighting of terminological units 153 13.11. Statistical properties of textual units: lexical laws 154 13.12. Sub-lexical units 155 13.14. Shallow parsing or superficial syntactic analysis 157 13.15. Argumentation models 158
• Chapter 14. Transversal Text Mining Techniques 159 14.1. Mixed and interdisciplinary text mining techniques 159 14.1.1. Supervised, unsupervised and semi-supervised techniques 159 14.2. Techniques for extraction of named entities 160 14.3. Inverse methods 163 14.4. Latent Semantic Analysis 164 14.5. Iterative construction of sub-corpora 165 14.6. Ordering approaches or ranking method 165 14.7. Use of ontology 166 14.8. Interdisciplinary techniques 167 14.9. Information visualization techniques 167 14.10. The k-means technique 168 14.11. Naive Bayes classifier technique 169 14.12. The k-nearest neighbors (KNN) technique 170 14.13. Hierarchical clustering technique 171 14.14. Density-based clustering techniques 172 14.15. Conditional fields 175 14.16. Nonlinear regression and artificial neural networks 176 14.17. Models of multi-agent systems (MASs) 177 14.18. Co-clustering models 178 14.19. Dependency models 179 14.20. Decision tree technique 179 14.21. The Support Vector Machine (SVM) technique 180 14.22. Set of frequent items 182 14.23. Genetic algorithms 184 14.24. Link analysis with a theoretical graph model 184 14.25. Link analysis without a graph model 185 14.26. Quality of a model 186 14.27. Model selection 189
• Chapter 15. Fields of Interest for Text Mining 191 15.1. The avenues in text mining 191 15.1.1. Organization 191 15.1.2. Discovery 193 15.2. About decision support 194 15.3. Competitive intelligence (vigilance) 195 15.4. About strategy 197 15.5. About archive management 200 15.6. About sociology and the legal field 203 15.7. About biology 215 15.8. About other domains 219 Conclusion 221 Bibliography 225 Index 267.
• (source: Nielsen Book Data)

This book presents a theory of consciousness which is unique and sustainable in nature, based on physiological and cognitive-linguistic principles controlled by a number of socio-psycho-economic factors. In order to anchor this theory, which draws upon various disciplines, the author presents a number of different theories, all of which have been abundantly studied by scientists from both a theoretical and experimental standpoint, including models of social organization, ego theories, theories of the motivational system in psychology, theories of the motivational system in neurosciences, language modeling and computational modeling of motivation. The theory presented in this book is based on the hypothesis that an individual s main activities are developed by self-motivation, managed as an informational need. This is described in chapters covering self-motivation on a day-to-day basis, the notion of need, the hypothesis and control of cognitive self-motivation and a model of self-motivation which associates language and physiology. The subject of knowledge extraction is also covered, including the impact of self-motivation on written information, non-transversal and transversal text-mining techniques and the fields of interest of text mining. Contents: 1. Consciousness: an Ancient and Current Topic of Study. 2. Self-motivation on a Daily Basis. 3. The Notion of Need. 4. The Models of Social Organization. 5. Self Theories. 6. Theories of Motivation in Psychology. 7. Theories of Motivation in Neurosciences. 8. Language Modeling. 9. Computational Modeling of Motivation. 10. Hypothesis and Control of Cognitive Self-Motivation. 11. A Model of Self-Motivation which Associates Language and Physiology. 12. Impact of Self-Motivation on Written Information. 13. Non-Transversal Text Mining Techniques. 14. Transversal Text Mining Techniques. 15. Fields of Interest for Text Mining. About the Authors Nicolas Turenne is a researcher at INRA in the Science and Society team at the University of Paris-Est Marne la Vallee in France. He specializes in knowledge extraction from texts with theoretical research into relational and stochastic models. His research topics also concern the sociology of uses, food and environmental sciences, and bioinformatics.
(source: Nielsen Book Data)

• Preface.
• 1. Introduction.
• 2. Information, meaning and representation.
• 3. Associative neural networks.
• 4. Circuit assemblies.
• 5. Machine perception.
• 6. Motor actions for robots.
• 7. Machine cognition.
• 8. Machine emotions.
• 9. Natural language in robot brains.
• 10. A cognitive architecture for robot brains.
• 11. Machine consciousness. Epilogue. References. Index.
• (source: Nielsen Book Data)

Haikonen envisions autonomous robots that perceive and understand the world directly, acting in it in a natural human-like way without the need of programs and numerical representation of information. By developing higher-level cognitive functions through the power of artificial associative neuron architectures, the author approaches the issues of machine consciousness. Robot Brains expertly outlines a complete system approach to cognitive machines, offering practical design guidelines for the creation of non-numeric autonomous creative machines. It details topics such as component parts and realization principles, so that different pieces may be implemented in hardware or software. Real-world examples for designers and researchers are provided, including circuit and systems examples that few books on this topic give. In novel technical and practical detail, this book also considers: * the limitations and remedies of traditional neural associators in creating true machine cognition; * basic circuit assemblies cognitive neural architectures; * how motors can be interfaced with the associative neural system in order for fluent motion to be achieved without numeric computations; * memorization, imagination, planning and reasoning in the machine; * the concept of machine emotions for motivation and value systems; * an approach towards the use and understanding of natural language in robots. The methods presented in this book have important implications for computer vision, signal processing, speech recognition and other information technology fields. Systematic and thoroughly logical, it will appeal to practising engineers involved in the development and design of robots and cognitive machines, also researchers in Artificial Intelligence. Postgraduate students in computational neuroscience and robotics, and neuromorphic engineers will find it an exciting source of information.
(source: Nielsen Book Data)

The next generation of computers are coming - and they're like nothing we've seen before. Scientists are turning away from silicon chips and instead are using real, wet, squishy, perhaps even living biology to build machines that could change the world forever. Cells, gels and DNA strands are the 'wetware' of the twenty-first century. Imagine taking cells from a cancer patient and programming them to be able to detect disease and prompt the body to cure itself. Or how about clothes woven with microchips and nanofibres to form wearable bio-weapons detection systems? Both revolutionary applications may be widespread in just ten years time. Exactly what breed of computer does the future hold? In this exhilarating book, the foremost expert in the field describes how this new technology will change the way we think - not just about computers, but about life itself.
(source: Nielsen Book Data)

• The Real Problem of Consciousness
• Consciousness and Subjective Experience
• Perception and Qualia
• From Perception to Consciousness
• Emotions and Consciousness
• Inner Speech and Consciousness
• Qualia and Machine Consciousness
• Testing Consciousness
• Artificial Conscious Cognition
• Associative Information Processing
• Neural Realization of Associative Processing
• Designing a Cognitive Perception System
• Examples of Perception/Response Feedback Loops
• The Transition to Symbolic Processing
• Information Integration with Multiple Modules
• Emotional Significance of Percepts
• The Outline of the Haikonen Cognitive Architecture (HCA)
• Mind Reading Applications
• The Comparison of Some Cognitive Architectures
• Example: An Experimental Robot with the HCA
• Concluding Notes
• Consciousness Explained.
• (source: Nielsen Book Data)

Robots are becoming more human, but could they also become sentient and have human-like consciousness?What is consciousness, exactly?It is a fact that our thoughts and consciousness are based on the neural activity of the brain. It is also a fact that we do not perceive our brain activity as it really is - patterns of neural firings. Instead, we perceive our sensations and thoughts apparently as they are. What kind of condition would transform the neural activity into this kind of internal appearance? This is the basic problem of consciousness.The author proposes an explanation that also provides preconditions for true conscious cognition - the requirement of a direct perceptive system with inherent sub-symbolic and symbolic information processing. Associative neural information processing with distributed signal representations is introduced as a method that satisfies these requirements.Conscious robot cognition also calls for information integration and sensorimotor integration. This requirement is satisfied by the Haikonen Cognitive Architecture (HCA).This book demystifies both the enigmatic philosophical issues of consciousness and the practical engineering issues of conscious robots by presenting them in an easy-to-understand manner for the benefit of students, researchers, philosophers and engineers in the field.
(source: Nielsen Book Data)

• Introduction: The psychic life of digital media
• Where is the writing of digital media? Why civilization matters
• Postmodernity and new media
• Thre conceptual lacunae
• Fundamental challenge to literary theory
• The techne of the unconscious
• The invention of printed English. How the English alphabet gained a new letter
• What is printed English?
• The genetic code and grammatology
• The ideographic turn of the phonetic alphabet
• The number game in the empires of the mind
• Sense and nonsense in the psychic machine. Finnegans wake: a hypermnesiac machine?
• Ispace: Joyce's paper wounds
• Schizoprenic writing at Bell Labs
• The cybernetics group
• The psychic machine
• The cybernetic unconscious. French theory or American theory?
• Lacan reading Poe: "the seminar on "The purloined letter""
• Les jeux: game and play on the symbolic chain
• The cybernetic unconscious. Return to sender
• The Freudian robot. The uncanny in the automaton
• The psychic life of media
• What is the medium of das Unheimliche?
• The uncanny valley
• The neurotic machine
• Minsky and the cognitive unconscious
• The future of the unconscious. The missed rendezvous between critical theory and cybernetics
• The ideology machine
• Our game with the little "letters."

The identity and role of writing has evolved in the age of digital media. But how did writing itself make digital media possible in the first place? Lydia H. Liu offers here the first rigorous study of the political history of digital writing and its fateful entanglement with the Freudian unconscious. Liu's innovative analysis brings the work of theorists and writers back into conversation with one another to document significant meetings of minds and disciplines. She shows how the earlier avant-garde literary experiments with alphabetical writing and the word-association games of psychoanalysis contributed to the mathematical making of digital media. Such intellectual convergence, she argues, completed the transformation of alphabetical writing into the post-phonetic, ideographic system of digital media, which not only altered the threshold of sense and nonsense in communication processes but also compelled a new understanding of human-machine interplay at the level of the unconscious. Ranging across information theory, cybernetics, modernism, literary theory, neurotic machines, and psychoanalysis, "The Freudian Robot" rewrites the history of digital media and the literary theory of the twentieth century.
(source: Nielsen Book Data)

• Table of Definitions vii Introduction ix
• Chapter 1. The Organizational Architecture of the Psychic System and the Feeling of Thinking 1 1.1. The problem of the study of thought 2 1.2. The interpretation of neuronal aggregates 5 1.3. The function of the architecture of the Freudian model 7 1.4. The specific characteristics of the components of the system using a constructivist approach 14 1.5. The systemic layer and the regulators 26 1.6. The mental landscape 35 1.7. The feeling of thinking and the general organizational principle 45 1.8. The aim and the space of the regulators 55 1.9. The attractors 67 1.10. The generation of a representation 74 1.11. Unification between regulators and neuronal aggregates: the morphological model of the generating forms 78 1.12. The morphological and semantic conformation of the psychic system 86 1.13. The processing component of the visual sense with generating forms 91 1.14. The decisive intention to think 97 1.15. Linguistic capacity in the human conscious 101 1.16. An assessment of the functioning of the human psychic system 109
• Chapter 2. The Computer Representation of an Artificial Consciousness 113 2.1. A multiagent design to generate an artificial psychic system 114 2.2. Designing the artificial psychic system using a multiagent approach 122 2.3. Self-control of the artificial psychic system using regulator agents 128 2.4. The organizational architecture of the system 133 2.5. Organizational memory and artificial experience 142 2.6. Affective and tendential states of the system 154 2.7. The production of representations and the sensation of thinking 161 2.7.1. Algorithm for the intentional production of a series of representations around a specific theme 163 2.8. The feeling of existing 176 2.9. The representation of the things and the apprehension of temporality 181 2.10. Multisystem deployment 186 2.11. The final fate of systems endowed with artificial consciousness 194 Conclusion 197 Bibliography 201 Index 205.
• (source: Nielsen Book Data)

This book will present a complete modeling of the human psychic system that allows to generate the thoughts in a strictly organizational approach that mixes a rising and falling approach. The model will present the architecture of the psychic system that can generate sensations and thoughts, showing how one can feel thoughts. The model developed into an organizational architecture based on massive multiagent systems. The architecture will be fully developed, showing how an artificial system can be endowed with consciousness and intentionally generate thoughts and, especially, feel them. These results are multidisciplinary, combining both psychology and computer science disciplines.
(source: Nielsen Book Data)

• Part 1 Birth of a new discipline - biocomputing: progress in computing
• tommorrow's computers
• expectations from the life sciences. Part 2 New developments in the life sciences: bioenergetics and biodevices
• information processing in biological organisms
• the neural circuitry of the brain
• thought and creativity. Part 3 General principles of biocomputers: biodevice computers
• learning from the brain to build a computer
• the creative computer. Part 4 Plans for biocomputers and society: the road towards realization of biocomputers
• the impact of the biocomputer
• recent developments in biocomputing projects in Japan.
• (source: Nielsen Book Data)

This book represents an up-to-date view of current interest in Japan in biocomputing. This branch of computing encompasses a switch in components, from silicon-based components to those which contain organic molecules. The book discusses the future of computing using silicon components and the technological capacities and the humanistic applications of biocomputing that may be possible once new carbon-based technologies are more fully developed. The book also contends that biocomputing is inherently linked to the technology of producing "artificial life". It suggests that the deeper understanding of cellular mechanisms which will allow the exploitation of the molecules of life in biocomputers, will inevitably be used to manipulate life forms to a far greater extent than is now possible in biotechnology. This kind of "artificial intelligence" holds much greater potential for exploring and possibly altering the evolution of biological forms than biocomputers themselves.
(source: Nielsen Book Data)

• Machine generated contents note: 1.1. Multidisciplinarity of the subject
• 1.2. Terminological outlook
• 1.3. Theological point of view
• 1.4. Notion of belief and autonomy
• 1.5. Scientific schools of thought
• 1.6. question of experience
• 2.1. In news blogs
• 2.2. Marketing
• 2.3. Appearance
• 2.4. Mystical experiences
• 2.5. Infantheism
• 2.6. Addiction
• 3.1. Hierarchy of needs
• 3.1.1. Level-1 needs
• 3.1.2. Level-3 needs
• 3.2. satiation cycle
• 4.1. entrepreneurial model
• 4.2. Motivational and ethical states
• 6.1. Behavior and cognition
• 6.2. Theory of self-efficacy
• 6.3. Theory of self-determination
• 6.4. Theory of control
• 6.5. Attribution theory
• 6.6. Standards and self-regulation
• 6.7. Deviance and pathology
• 6.8. Temporal Motivation Theory
• 6.9. Effect of objectives
• 6.10. Context of distance learning
• 6.11. Maintenance model
• 6.12. Effect of narrative
• 6.13. Effect of eviction
• 6.14. Effect of the teacher-student relationship
• 6.15. Model of persistence and change
• 6.16. Effect of the man-machine relationship
• 7.1. Academic literature on the subject
• 7.2. Psychology and Neurosciences
• 7.3. Neurophysiological theory
• 7.4. Relationship between the motivational system and the emotions
• 7.5. Relationship between the motivational system and language
• 7.6. Relationship between the motivational system and need
• 8.1. Issues surrounding language
• 8.2. Interaction and language
• 8.3. Development and language
• 8.4. Schools of thought in linguistic sciences
• 8.5. Semantics and combination
• 8.6. Functional grammar
• 8.7. Meaning-Text Theory
• 8.8. Generative lexicon
• 8.9. Theory of synergetic linguistics
• 8.10. Integrative approach to language processing
• 8.11. New spaces for date production
• 8.12. Notion of ontology
• 8.13. Knowledge representation
• 9.1. Notion of a computational model
• 9.2. Multi-agent systems
• 9.3. Artificial self-organization
• 9.4. Artificial neural networks
• 9.5. Free will theorem
• 9.6. probabilistic utility model
• 9.7. autoepistemic model
• 10.1. Social groups
• 10.2. Innate self-motivation
• 10.3. Mass communication
• 10.4. Cost-Benefit ratio
• 10.5. Social representation
• 10.6. relational environment
• 10.7. Perception
• 10.8. Identity
• 10.9. Social environment
• 10.10. Historical antecedence
• 10.11. Ethics
• 11.1. new model
• 11.2. Architecture of a self-motivation subsystem
• 11.3. Level of certainty
• 11.4. Need for self-motivation
• 11.5. Notion of motive
• 11.6. Age and location
• 11.7. Uniqueness
• 11.8. Effect of spontaneity
• 11.9. Effect of dependence
• 11.10. Effect of emulation
• 11.11. Transition of belief
• 11.12. Effect of individualism
• 11.13. Modeling of the groups of beliefs
• 12.1. Platform for production and consultation of texts
• 12.2. Informational measure of the motives of self-motivation
• 12.2.1. Intra-phrastic extraction
• 12.2.2. Inter-phrastic extraction
• 12.2.3. Meta-phrastic extraction
• 12.3. information market
• 12.4. Types of data
• 12.5. outlines of text mining
• 12.6. Software economy
• 12.7. Standards and metadata
• 12.8. Open-ended questions and challenges for text-mining methods
• 12.9. Notion of lexical noise
• 12.10. Web mining
• 12.11. Mining approach
• 13.1. Constructivist activity
• 13.2. Typicality associated with the data
• 13.3. Specific character of text mining
• 13.4. Supervised, unsupervised and semi-supervised techniques
• 13.5. Quality of a model
• 13.6. scenario
• 13.7. Representation of a datum
• 13.8. Standardization
• 13.9. Morphological preprocessing
• 13.10. Selection and weighting of terminological units
• 13.11. Statistical properties of textual units: lexical laws
• 13.12. Sub-lexical units
• 13.14. Shallow parsing or superficial syntactic analysis
• 13.15. Argumentation models
• 14.1. Mixed and interdisciplinary text mining techniques
• 14.1.1. Supervised, unsupervised and semi-supervised techniques
• 14.2. Techniques for extraction of named entities
• 14.3. Inverse methods
• 14.4. Latent Semantic Analysis
• 14.5. Iterative construction of sub-corpora
• 14.6. Ordering approaches or ranking method
• 14.7. Use of ontology
• 14.8. Interdisciplinary techniques
• 14.9. Information visualization techniques
• 14.10. k-means technique
• 14.11. Naive Bayes classifier technique
• 14.12. k-nearest neighbors (KNN) technique
• 14.13. Hierarchical clustering technique
• 14.14. Density-based clustering techniques
• 14.15. Conditional fields
• 14.16. Nonlinear regression and artificial neural networks
• 14.17. Models of multi-agent systems (MASs)
• 14.18. Co-clustering models
• 14.19. Dependency models
• 14.20. Decision tree technique
• 14.21. Support Vector Machine (SVM) technique
• 14.22. Set of frequent items
• 14.23. Genetic algorithms
• 14.24. Link analysis with a theoretical graph model
• 14.25. Link analysis without a graph model
• 14.26. Quality of a model
• 14.27. Model selection
• 15.1. avenues in text mining
• 15.1.1. Organization
• 15.1.2. Discovery
• 15.2. About decision support
• 15.3. Competitive intelligence (vigilance)
• 15.4. About strategy
• 15.5. About archive management
• 15.6. About sociology and the legal field
• 15.7. About biology
• 15.8. About other domains.

This book presents a theory of consciousness which is unique and sustainable in nature, based on physiological and cognitive-linguistic principles controlled by a number of socio-psycho-economic factors. In order to anchor this theory, which draws upon various disciplines, the author presents a number of different theories, all of which have been abundantly studied by scientists from both a theoretical and experimental standpoint, including models of social organization, ego theories, theories of the motivational system in psychology, theories of the motivational system in neurosciences, language modeling and computational modeling of motivation. The theory presented in this book is based on the hypothesis that an individual s main activities are developed by self-motivation, managed as an informational need. This is described in chapters covering self-motivation on a day-to-day basis, the notion of need, the hypothesis and control of cognitive self-motivation and a model of self-motivation which associates language and physiology. The subject of knowledge extraction is also covered, including the impact of self-motivation on written information, non-transversal and transversal text-mining techniques and the fields of interest of text mining. Contents: 1. Consciousness: an Ancient and Current Topic of Study. 2. Self-motivation on a Daily Basis. 3. The Notion of Need. 4. The Models of Social Organization. 5. Self Theories. 6. Theories of Motivation in Psychology. 7. Theories of Motivation in Neurosciences. 8. Language Modeling. 9. Computational Modeling of Motivation. 10. Hypothesis and Control of Cognitive Self-Motivation. 11. A Model of Self-Motivation which Associates Language and Physiology. 12. Impact of Self-Motivation on Written Information. 13. Non-Transversal Text Mining Techniques. 14. Transversal Text Mining Techniques. 15. Fields of Interest for Text Mining. About the Authors Nicolas Turenne is a researcher at INRA in the Science and Society team at the University of Paris-Est Marne la Vallee in France. He specializes in knowledge extraction from texts with theoretical research into relational and stochastic models. His research topics also concern the sociology of uses, food and environmental sciences, and bioinformatics.
(source: Nielsen Book Data)

• Introduction
• The Road to Intelligence
• Cybernetics
• Symbolic AI: The Golden Age
• Diaspora
• The New Synthesis
• Beyond Human Ken?
• Autogeny
• Representation and Search
• Fun and Games
• Design and Learning
• Analogy and Perception
• Design for a Brain
• An Economy of Mind
• Kinds of Minds
• When
• Philosophical Extrapolations
• Evolutionary Ethics
• Asimov's Three Laws of Robotics
• The Age of Virtuous Machines
• Profiles of the Future
• index.
• (source: Nielsen Book Data)

Artificial intelligence (AI) is now advancing at such a rapid clip that it has the potential to transform our world in ways both exciting and disturbing. Computers have already been designed that are capable of driving cars, playing soccer, and finding and organising information on the Web in ways that no human could. With each new gain in processing power, will scientists soon be able to create supercomputers that can read a newspaper with understanding, or write a news story, or create novels, or even formulate laws. And if machine intelligence advances beyond human intelligence, will we need to start talking about a computer's intentions. These are some of the questions discussed by computer scientist J Storrs Hall in this fascinating layperson's guide to the latest developments in artificial intelligence. Drawing on a thirty-year career in artificial intelligence and computer science, Hall reviews the history of AI, discussing some of the major roadblocks that the field has recently overcome, and predicting the probable achievements in the near future. There is new excitement in the field over the amazing capabilities of the latest robots and renewed optimism that achieving human-level intelligence is a reachable goal. But what will this mean for society and the relations between technology and human beings? Soon ethical concerns will arise and programmers will need to begin thinking about the computer counterparts of moral codes and how ethical interactions between humans and their machines will eventually affect society as a whole. Weaving disparate threads together in an enlightening manner from cybernetics, computer science, psychology, philosophy of mind, neurophysiology, game theory, and economics, Hall provides an intriguing glimpse into the astonishing possibilities and dilemmas on the horizon.
(source: Nielsen Book Data)