Artificial intelligence in the age of neural networks and brain computing

Chapter 1Nature'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 1...
Ausführliche Beschreibung

Chapter 1Nature'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 2A 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 3Third Gen AI as human experience based expert systems /Harold Szu and the AI working group --Introduction --Third gen AI --MFE gradient descent --Conclusion --4The brain-mind-computer trichotomy: Hermeneutic approach /Péter Érdi --Dichotomies --Hermeneutics --Schizophrenia: A broken hermeneutic cycle --Toward the algorithms of neural/mental hermeneutic interpretation --Chapter 5From synapses to ephapsis: Embodied cognition and wearable personal assistants / Roman Ormandy --Neural networks and neural fields --Ephapsis --Embodied cognition --Wearable personal assistants --References --Chapter 6Evolving 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 7Pitfalls 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 8The 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 9Theory 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 10Computers 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 11Deep 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 12Computational 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 13Multiview 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 14Meaning 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 15Evolving 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. Ausführliche Beschreibung

Autor*in:	Alippi, Cesare [herausgeberIn] Morabito, Francesco Carlo [herausgeberIn] Choe, Yoonsuck [herausgeberIn]

Format:	E-Book
Sprache:	Englisch

Erschienen:	London, United Kingdom: Academic Press, an imprint of Elsevier ; 2019

Schlagwörter:	Neural networks (Computer science) Brain-computer interfaces Artificial intelligence Artificial Intelligence Neural Networks, Computer COMPUTERS ; General Intelligence artificielle Réseaux neuronaux (Informatique) Interfaces cerveau-ordinateur
Formangabe:	Electronic books

Anmerkung:	Includes index
Umfang:	1 Online-Ressource

Links:	Link aufrufen Volltext Volltext Link aufrufen
ISBN:	0-12-816250-3

Katalog-ID:	1685484816