Future Directions for Intelligent Systems and Information Sciences

by Kasabov, Nikola

• ISBN13: 9783790812763
• ISBN10: 3790812765
• eBook ISBN(s): 9783790818567
• Format: Hardcover
• Copyright: 2000-08-01
• Publisher: Physica Verlag
• More Book Details
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Summary

The book introduces and discusses the future trends in computer science and artificial intelligence. These trends include image and speech technologies; virtual reality and multimedia systems; evolving systems and artificial life; artificial and natural neural networks; brain-computers; the Web, the intelligent agents on it, and the distributed processing systems; mobile robots in a real and in a virtual environment; bioinformatics, and the marriage of genetic engineering and information science. The book comprises chapters written by well-known specialists in this field and can be used by scientists and graduate students from different areas, as well as by a wider audience of people interested in the present and future development of intelligent systems, in all areas of information sciences.

Table of Contents

Part I: Adaptive, evolving, learning systems
ECOS - Evolving Connectionist Systems - a new/old paradigm for on-line learning and knowledge engineering	3	(10)
N. Kasabov
Artificial life technology for adaptive information processing	13	(21)
Sung-Bae Cho
Evolving ANN controllers for smart mobile robots	34	(31)
R.J. Duro
J. Santos
J.A. Becerra
A simulation environment for the manipulation of naturally variable objects	65	(10)
G. Coghill
Behavior-decision fuzzy algorithm for autonomous mobile robot	75	(27)
Y. Maeda
Modelling the emergence of speech and language through evolving connectionist systems	102	(27)
J. Taylor
N. Kasabov
Part II: Intelligent human computer interaction and scientific visualisation
Discovering the visual signature of painters	129	(19)
H.J. van den Herik
E. O. Postma
Multimodal interactions with agents in virtual worlds	148	(26)
A. Nijhollt
J. Hulstijn
Virtual BioBots	174	(17)
M. Paulin
R. Berquist
Part III: New connectionist computational paradigms: Brainlike computing and quantum neural networks
Future directions for neural networks and intelligent systems from the brain imaging research	191	(22)
J.G. Taylor
Quantum neural networks	213	(23)
A.A. Ezhov
D. Ventura
Suprathreshold stochastic resonance in a neuronal network model: a possible strategy for sensory coding	236	(15)
N.G. Stocks
R. Mannella
Part IV: Bioinformatics
Information science and bioinformatics	251	(37)
C. Brown
M. Schreiber
B. Chapman
G. Jacobs
Neural network system for promoter recognition	288	(21)
V.B. Bajic
I.V. Bajic
Part V: Knowledge representation, knowledge processing, knowledge discovery, and some applications
Granular computing: An introduction	309	(20)
W. Pedrycz
A new paradigm shift from computation on numbers to computation on words on an example of linguistic database summarization	329	(18)
J.Kacprzyk
Hybrid intelligent decision support systems and applications for risk analysis and discovery of evolving economic clusters in Europe	347	(26)
N. Kasabov
L. Erzegovesi
M. Fedrizzi
A. Beber
D. Deng
Intelligent resource management through the constrained resource planning model	373	(14)
D.Y.Y. Yun
Evaluative studies of fuzzy knowledge discovery through NF systems	387
A.Ramer
M. do Carmo Nicoletti
S.Y. Sung