Future Directions For Intelligent Systems And Information Sciences: The Future Of Speech And Image Technologies, Brain Computers, Www, And Bioinformatics (studies In Fuzziness And Soft Computing)

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. Front Matter....Pages I-VIII Front Matter....Pages 1-1 ECOS — Evolving Connectionist Systems — a New/Old Paradigm for On-line Learning and Knowledge Engineering....Pages 3-12 Artificial Life Technology for Adaptive Information Processing....Pages 13-33 Evolving ANN Controllers for Smart Mobile Robots....Pages 34-64 A Simulation Environment for the Manipulation of Naturally Variable Objects....Pages 65-74 Behavior-Decision Fuzzy Algorithm for Autonomous Mobile Robot....Pages 75-101 Modelling the Emergence of Speech and Language Through Evolving Connectionist Systems....Pages 102-125 Front Matter....Pages 127-127 Discovering the Visual Signature of Painters....Pages 129-147 Multimodal Interactions with Agents in Virtual Worlds....Pages 148-173 Virtual BioBots....Pages 174-187 Front Matter....Pages 189-189 Future Directions for Neural Networks and Intelligent Systems from the Brain Imaging Research....Pages 191-212 Quantum Neural Networks....Pages 213-235 Suprathreshold Stochastic Resonance in a Neuronal Network Model: a Possible Strategy for Sensory Coding....Pages 236-247 Front Matter....Pages 249-249 Information Science and Bioinformatics....Pages 251-287 Neural Network System for Promoter Recognition....Pages 288-305 Front Matter....Pages 307-307 Granular Computing : An Introduction....Pages 309-328 A New Paradigm Shift from Computation on Numbers to Computation on Words on an Example of Linguistic Database Summarization....Pages 329-346 Hybrid Intelligent Decision Support Systems and Applications for Risk Analysis and Discovery of Evolving Economic Clusters in Europe....Pages 347-372 Intelligent Resource Management Through the Constrained Resource Planning Model....Pages 373-386 Evaluative Studies of Fuzzy Knowledge Discovery through NF Systems....Pages 387-411 Back Matter....Pages 412-412 This edited volume comprises invited chapters that cover five areas of the current and the future development of intelligent systems and information sciences. Half of the chapters were presented as invited talks at the Workshop "Future Directions for Intelligent Systems and Information Sciences" held in Dunedin, New Zealand, 22-23 November 1999 after the International Conference on Neuro-Information Processing (lCONIPI ANZIISI ANNES '99) held in Perth, Australia. In order to make this volume useful for researchers and academics in the broad area of information sciences I invited prominent researchers to submit materials and present their view about future paradigms, future trends and directions. Part I contains chapters on adaptive, evolving, learning systems. These are systems that learn in a life-long, on-line mode and in a changing environment. The first chapter, written by the editor, presents briefly the paradigm of Evolving Connectionist Systems (ECOS) and some of their applications. The chapter by Sung-Bae Cho presents the paradigms of artificial life and evolutionary programming in the context of several applications (mobile robots, adaptive agents of the WWW). The following three chapters written by R.Duro, J.Santos and J.A.Becerra (chapter 3), GCoghill . (chapter 4), Y.Maeda (chapter 5) introduce new techniques for building adaptive, learning robots.