TY  - BOOK
AU  - Hoya,Tetsuya
ED  - SpringerLink (Online service)
TI  - Artificial Mind System - Kernel Memory Approach
T2  - Studies in Computational Intelligence,
SN  - 9783540324034
AV  - TA329-348 
U1  - 519 23
PY  - 2005///
CY  - Berlin, Heidelberg
PB  - Springer Berlin Heidelberg
KW  - Engineering
KW  - Artificial intelligence
KW  - Bioinformatics
KW  - Physics
KW  - Engineering mathematics
KW  - Vibration
KW  - Biomedical engineering
KW  - Appl.Mathematics/Computational Methods of Engineering
KW  - Artificial Intelligence (incl. Robotics)
KW  - Complexity
KW  - Vibration, Dynamical Systems, Control
KW  - Biomedical Engineering
N1  - Part I: The Neural Foundations -- From Classical Connectionist Models to Probabilistic / Generalised Regression Neural Networks (PNNs / GRNNs) -- The Kernel Memory Concept – A Paradigm Shift from Conventional Connectionism -- The Self-Organising Kernel Memory (SOKM) -- Part II: Artificial Mind Systems -- The Artificial Mind System (AMS), Modules, and their Interactions -- Sensation and Perception Modules -- Learning in the AMS Context -- Memory Modules and the Innate Structure -- Language and Thinking Modules -- Modelling Abstract Notions Relevant to the Mind and Associated Modules -- Epilogue – Towards Developing a Realistic Sense of Artificial Intelligence
N2  - This book is written from an engineer's perspective of the mind. "Artificial Mind System" exposes the reader to a broad spectrum of interesting areas in general brain science and mind-oriented studies. In this research monograph a picture of the holistic model of an artificial mind system and its behaviour is drawn, as concretely as possible, within a unified context, which could eventually lead to practical realisation in terms of hardware or software. With a view that "the mind is a system always evolving", ideas inspired by many branches of studies related to brain science are integrated within the text, i.e. artificial intelligence, cognitive science / psychology, connectionism, consciousness studies, general neuroscience, linguistics, pattern recognition / data clustering, robotics, and signal processing
UR  - http://dx.doi.org/10.1007/b96963
ER  -