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The application section covers a wide range of topics, including applications to environmental management, biology and medicine, neural networks, collaborative visualization and intelligent interfaces. The book consists of 13 invited chapters written by former colleagues and students of Professor Karplus. 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The goal is to build  robots which can emulate the ability of living organisms to integrate  perceptual inputs smoothly with motor responses, even in the presence  of novel stimuli and changes in the environment. The ability of living  systems to learn and to adapt provides the standard against which  robotic systems are judged. In order to emulate these abilities, a  number of investigators have attempted to create robot controllers  which are modelled on known processes in the brain and  musculo-skeletal system. Several of these models are described in this  book.    On the other hand, connectionist (artificial neural network)  formulations are attractive for the computation of inverse kinematics  and dynamics of robots, because they can be trained for this purpose  without explicit programming. Some of the computational advantages and  problems of this approach are also presented.    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