Neural Networks and Natural Intelligence. Este artículo no está disponible.Neural Networks and Natural Intelligence

Book by Grossberg Stephen

Stephen Grossberg and his colleagues at Boston University's Center for Adaptive Systems are producing some of the most exciting research in the neural network approach to making computers "think." Packed with real-time computer simulations and rigorous demonstrations of these phenomena, this book includes results on vision, speech, cognitive information processing, adaptive pattern recognition, adaptive robotics, conditioning and attention, cognitive-emotional interactions, and decision making under risk."Neural Networks and Natural Intelligence" first discusses neural network architecture for preattentive 3-D vision then shows how this architecture provides a unified explanation, through systematic computer simulations, of many classical and recent phenomena from psychophysics, visual perception, and cortical neurophysiology. It illustrates within the domain of preattentive boundary segmentation and featural filling-in, how computer experiments help to develop and refine computational vision models.Chapters next address a higher level of cognitive processing. They provide a historical and comparative analysis of several recent types of models - competitive learning, interactive activation, adaptive resonance, and back propagation architectures - and describe mathematical and computer analyses of self-organizing multiple-scale cognitive recognition codes. While playing a role in vision processing, these architectures for cognitive recognition codes also form a part of a larger theory which includes speech and language processing. This theory is summarized in a chapter that analyzes the processing level for encoding item and temporal order information in working memory by quantitativelysimulating difficult data about this process.Shifting to an analysis of how cognitive processing and reinforcement interact to focus attention upon emotionally salient and cognitively predictive cues, chapters illustrate that with the neural network theory there is no bottleneck to joining information processing and appetitive mechanisms. Final chapters describe the ability of these cognitive-emotional interactions to explain data about decision making under risk, and describe the developmental, learning, and automatic processes which control the accuracy and timing of planned arm movements.Stephen Grossberg is Professor of Mathematics, Psychology, and Biomedical Engineering and Director of the Center for Adaptive Systems at Boston University. A Bradford Book.