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Artificial intelligence in the age of neural networks and brain computing /
With contributions from pioneers and experts in the field of neural networks, this book covers the major basic ideas of brain-like computing behind AI, provides a framework to deep learning, and launches novel and intriguing paradigms as future alternatives. --
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | , , , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
London, United Kingdom :
Academic Press, an imprint of Elsevier,
[2019]
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| Temas: | |
| Acceso en línea: | Texto completo Texto completo |
Tabla de Contenidos:
- Chapter 1 Nature's learning rule: The Hebbian-LMS algorithm / Bernard Widrow, Youngsik Kim, Dookun Park and Jose Krause Perin
- Introduction
- ADALINE and the LMS algorithm, From the 1950s
- Unsupervised learning with Adaline, From the 1960s
- Robert Lucky's adaptive equalization, From the 1960s
- Bootstrap learning with a Sigmoidal neuron
- Bookstrap learning with a more "Biologically correct" Sigmoidal neuron
- Other clustering algorithms
- A general Hebbian-LMS algorithm
- The synapse
- Postulates of synaptic plasticity
- The postulates and the Hebbian-LMS algorithm
- Nature's Hebbian-LMS algorithm
- Conclusion
- Chapter 2 A half century of progress toward a unified neural theory of mind and brain with applications to autonomous adaptive agents and mental disorders / Stephen Grossberg
- Towards a unified theory of mind and brain
- A theoretical method for linking brain to mind: The method of minimal anatomies
- Revolutionary brain paradigms: Complementary computing and laminar computing
- The what and where cortical streams are complementary
- Adaptive resonance theory
- Vector associative maps for spatial representation and action
- Homologous laminar cortical circuits for all biological intelligence: Beyond Bayes
- Why a unified theory is possible: Equations, modules, and architectures
- All conscious states are resonant states
- The varieties of brain resonances and the conscious experiences that they support
- Why does resonance trigger consciousness?
- Towards autonomous adaptive intelligent agents and clinical therapies in society
- References
- Chapter 3 Third Gen AI as human experience based expert systems / Harold Szu and the AI working group
- Introduction
- Third gen AI
- MFE gradient descent
- Conclusion
- 4 The brain-mind-computer trichotomy: Hermeneutic approach / �Pter �rdi
- Dichotomies
- Hermeneutics
- Schizophrenia: A broken hermeneutic cycle
- Toward the algorithms of neural/mental hermeneutic interpretation
- Chapter 5 From synapses to ephapsis: Embodied cognition and wearable personal assistants / Roman Ormandy
- Neural networks and neural fields
- Ephapsis
- Embodied cognition
- Wearable personal assistants
- References
- Chapter 6 Evolving and spiking connectionist systems for brain-inspired artificial intelligence / Nikola Kasabov
- From Aristotle's logic to artificial neural networks and hybrid systems
- Evolving connectionist systems (ECOS)
- Spiking neural networks (SNN) as brain-inspired ANN
- Brain-like AI systems based on SNN, NeuCube, deep learning algorithms
- Conclusion
- Chapter 7 Pitfalls and opportunities in the development and evaluation of artificial intelligence systems / David G. Brown and Frank W. Samuelson
- Introduction
- AI development
- AI evaluation
- Variability and bias in our performance estimates
- Conclusion
- Chapter 8 The new AI: Basic concepts, urgent risks and opportunities in the Internet of Things / Paulo J. Werbos
- Introduction and overview
- Brief history and foundations of the deep learning revolution
- From RNNs to mouse-level computational intelligence: Next big things and beyond
- Need for new directions in understanding brain and mind
- Information technology (IT) for human survival: An urgent unmet challenge
- References
- Chapter 9 Theory of the brain and mind: Visions and history / Daniel S. Levine
- Early history
- Emergence of some neural network principles
- Neural networks enter mainstream science
- Is computational neuroscience separate from neural network theory?
- Discussion
- References
- Chapter 10 Computers versus brains: Game is over or more to come? / Robert Kozma
- Introduction
- AI approaches
- Metastability in cognition and in brain dynamics
- Pragmatic implementation of complementarity for new AI
- Acknowledgments
- References
- Chapter 11 Deep learning apporaches to electrophysiological multivariate time-series analysis / Francesco Carlo Morabito, Maurizio Campolo, Cosimo leracitano and Nadia Mammone
- Introduction
- The neural network approach
- Deep architectures and learning
- Electrophysiological time-series
- Deep learning models for EEG signal processing
- Future directions of research
- Conclusion
- Further reading
- Chapter 12 Computational intelligence in the time of cyber-physical systems and the Internet of Things / Cesare Alippi and Seiichi Ozawa
- Introduction
- System architecture
- Energy harvesting and management
- Learning in nonstationary environments
- Model-free fault diagnosis systems
- Cybersecurity
- Conclusions
- Acknowledgments
- References
- Chapter 13 Multiview learning in biomedical applications / Angela Serra, Paola Galdi and Roberto Tagliaferri
- Introduction
- Multiview learning
- Multiview learning in bioinformatics
- Multiview learning in neuroinformatics
- Deep multimodal feature learning
- Conclusions
- References
- Chapter 14 Meaning versus information, prediction versus memory, and question versus answer / Yoonsuck Choe
- Introduction
- Meaning versus information
- Prediction versus memory
- Question versus answer
- Discussion
- Conclusion
- Acknowledgments
- References
- Chapter 15 Evolving deep neural networks / Risto Miikkulainen, Jason Liang, Elliot Meyerson, Aditya Rawal, Daniel Fink, Olivier Francon, Bala Raju, Hormoz Shahrzad, Arshak Navruzyan, Nigel Duffy and Babak Hodjat
- Introduction
- Background and related work
- Evolution of deep learning architectures
- Evolution of LSTM architectures
- Evolution of LSTM architectures
- Application case study: Image captioning for the blind
- Discussion and future work
- Conclusion
- References.