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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.

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.

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

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