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Evolvable Biologically Plausible Visual Architectures

Aaron Sloman

Year
2001
Citations
27

Abstract

Much work in AI is fragmented, partly because the subject is so huge that it is difficult for anyone to think about all of it. Even within sub-fields, such as language, reasoning, and vision, there is fragmentation, as the sub-sub-fields are rich enough to keep people busy all their lives. However, there is a risk that results of isolated research will be unsuitable for future integration, e.g. in models of complete organisms, or human like robots. This paper offers a framework for thinking about the many components of visual systems and how they relate to the whole organism or machine. The viewpoint is biologically inspired, using conjectured evolutionary history as a guide to some of the features of the architecture. It may also be useful both for modelling animal vision and designing robots with similar capabilities. 1

Keywords

Computer scienceRobotArtificial intelligenceArchitectureHuman–computer interactionBiological organismCognitive scienceData scienceEngineeringBiological materials

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