What Should Be Computed to Understand and Model Brain Function? : From Robotics, Soft Computing, Biology and Neuroscience to Cognitive Philosophy.
Title:
What Should Be Computed to Understand and Model Brain Function? : From Robotics, Soft Computing, Biology and Neuroscience to Cognitive Philosophy.
Author:
Kitamura, Tadashi.
ISBN:
9789812810304
Personal Author:
Physical Description:
1 online resource (323 pages)
Series:
Fuzzy Logic Systems Institute (Flsi) Soft Computing Series ; v.3
Fuzzy Logic Systems Institute (Flsi) Soft Computing Series
Contents:
Contents -- Series Editor's Preface -- Volume Editor's Preface -- Chapter 1 Consideration of Emotion Model and Primitive Language of Robots -- 1.1 Introduction -- 1.2 Acquisition Algorithm of World Model of Robots -- 1.3 Primitive Language -- 1.4 Autonomous Robot: WAMOEBA-2 -- 1.5 Communication of WAMOEBA-2 -- 1.6 Model Acquisition Algorithm of WAMOEBA-2 -- 1.7 Diversification of Expression -- 1.8 Evaluation Experiment -- 1.9 Conclusion and Further Perspectives -- References -- Chapter 2 An Architecture for Animal-like Behavior Selection -- 2.1 Introduction -- 2.2 Architechture(CBA) -- 2.3 Criteria for Behavior Selection -- 2.4 Behavior Design -- 2.5 Experiments -- 2.6 Discussion -- 2.7 Conclusion -- References -- Chapter 3 A Computational Literary Theory: The Ultimate Products of the Brain/Mind Machine -- 3.1 Introduction -- 3.2 Literary Text and Cognition -- 3.3 Literary Computing -- 3.4 Conclusions -- References -- Chapter 4 Cooperation between Neural Networks within the Brain -- 4.1 Introduction -- 4.2 Cerebral Cortex : the 'Pilot' -- 4.3 Cerebellar Cortex : the 'Smoother Computer' -- 4.4 Basal Ganglia : the 'Security' Computer -- 4.5 Conclusion -- References -- Chapter 5 Brain-like Functions in Evolving Connectionist Systems for On-line Knowledge-Based Learning -- 5.1 Introduction: What Brain-like Functions and Principles to Implement in Intelligent Information Systems? -- 5.2 The ECOS Framework -- 5.3 Evolving Fuzzy Neural Networks EFuNNs -- 5.4 EFuNNs as Universal Learning Machines. Local and Global Generalisation -- 5.5 Conclusions and Directions for Further Research -- References -- Chapter 6 Interrelationships, Communication, Semiotics and Artificial Consciousness -- 6.1 Introduction -- 6.2 State of the Art.
6.3 Several Desirable Properties and Current Limits of the Current Machines -- 6.4 The Sensitive Computer -- 6.5 Perception, Self-representation and Self-relating -- 6.6 Relationship and Relationship Representation: Key Factors in Intelligence and Communication -- 6.7 Methods to Embed Relationships -- 6.8 Technical Means -- 6.9 Conclusions and Future Perspectives -- References -- Chapter 7 Time Emerges from Incomplete Clock Based on Internal Measurement -- 7.1 Introduction -- 7.2 Distinction by Invalidating Distinction -- 7.3 Punctuated Equilibrium Resulting Asynchronous Clock -- 7.4 Origin of Time -- 7.5 Conclusion -- References -- Chapter 8 The Logical Jump in Shell Changing in Hermit Crab and Tool Experiment in the Ants -- 8.1 Introduction -- 8.2 A Relationship between a Self-similarity and a Paradox -- 8.3 Methods -- 8.4 Results -- 8.5 Conclusion and Future Perspective -- References -- Chapter 9 The Neurobiology of Semantics: How Can Machines be Designed to Have Meanings? -- 9.1 Introduction -- 9.2 Communication by Representations -- 9.3 Observations of Electroencephalograms -- 9.4 The Neural Basis for Intentional Action -- 9.5 Linear versus Circular Causality -- 9.6 A Hypothesis on the Causal Relations of Meanings and Representations -- 9.7 Conclusion -- References -- Chapter 10 The Emergence of Contentful Experience -- 10.1 Introduction -- 10.2 Function -- 10.3 Representation -- 10.4 Brain and Mind: Some Relations -- 10.5 Conclusions -- References -- Chapter 11 Intentionality and Foundations of Logic: A New Approach to Neurocomputation -- 11.1 Introduction -- 11.2 Intentionality and Cognitive Neuroscience -- 11.3 Intentionality and Foundations of Logic after Godel -- 11.4 Conclusion -- References -- About the Authors -- Keyword Index.
Abstract:
This volume is a guide to two types of transcendence of academic borders which seem necessary for understanding and modelling brain function. The first type is technical transcendence needed to make intelligent machines such as a humanoid robot, an animal-like behavior architecture, an interpreter of fiction, and an evolving learning machine. This technical erosion is conducted into areas such as biology, ethology, neuroscience and psychology, as well as robotics and soft computing. The second type of transcendence of cross-disciplinary boundaries cuts across scientific areas such as biology and cognitive science/philosophy, into comprehensive, less technical and more abstract aspects of brain function. These aspects enable us to know in what direction and how far an intelligent machine will go. Contents: Consideration of Emotion Model and Primitive Language of Robots (T Ogata & S Sugano); An Architecture for Animal-Like Behavior Selection (T Kitamura); A Computational Literary Theory: The Ultimate Products of the Brain/Mind Machine (A Tokosumi); Cooperation Between Neural Networks Within the Brain (M Dufossé et al.); Brain-Like Functions in Evolving Connectionist Systems for On-Line, Knowledge-Based Learning (N Kasabov); Interrelationships, Communication, Semiotics, and Artificial Consciousness (H-N L Teodorescu); Time Emerges from Incomplete Clock, Based on Internal Measurement (Y-P Gunji et al.); The Logical Jump in Shell Changing in Hermit Crab and Tool Experiment in Ants (N Kitabayashi et al.); The Neurobiology of Semantics: How Can Machines be Designed to Have Meanings (W J Freeman); The Emergence of Contentful Experience (M H Bickhard); Intentionality and Foundations of Logic: A New Approach to Neurocomputation (G Basti). Readership: Graduate students, researchers and academics in robotics automated systems, biomedical engineering and
bioengineering.
Local Note:
Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2017. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
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Electronic Access:
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