Spatiotemporal Models In Biological And Artificial Systems
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Spatiotemporal Models in Biological and Artificial Systems
Spatiotemporal models are emerging as a very important topic in several disciplines, including neurobiology and artificial neural networks. Many hard problems exist in this area. Examples include understanding the capabilities of nonlinear dynamical systems on a lattice and of networks of spiking neurons (both natural and artificial), training such systems, implementing them in hardware, understanding biological signals like the EEG, etc. Besides the state-of-the-art in the area of spatiotemporal models, the book also covers the neurobiological, and the artificial systems communities.
GIS and GeoComputation
Geographic Information Systems are computer-based systems for geographic analysis. They have been developed over the past twenty five years and are now widely used. A recent research direction has been the development of geocomputation , representing computer-based geographical analysis beyond the traditional bounds of GIS. In geocomputation, the computer is the research environment itself, not merely a tool. A key to geocomputation it that highly powered computing can be used with sufficient data to avaid traditional parametric approaches altogether. The term geocomputation includes the use of computer-based techniques such as artificial neural networks, genetic programming and fuzzy logic, but in a geographical context. This new book in the prestigious Innovations in GIS series, presents the latest research in geocomputational techniques as presented in the GIS UK Annual Conference.
Seventh Scandinavian Conference on Artificial Intelligence
The 7th Scandanavian Conference on Artificial Intelligence, held at the Maersk McKinney Moller Institute for Production Technology at the University of Southern Denmark, Odense, in Feb 2001 continued a tradition established by SCAI of being an important conference in Europe. It attracted submissions from all over the world. Contents include: robotics; sensor/motor intelligence; evolutionary robotics; behaviour-based systems; multi-agent systems; applications of AI in bioinformatics; soft computing and heuristic algorithms, where paradigms from nature are used to build learning and optimization systems; and control and optimization.