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Abstract:
The development of autonomous as well as situated robots is one of the great remaining challenges and involves a number of different scientific disciplines. In spite of
recent dramatic progress, it remains worthwhile to examine natural systems, because their abilities are still out of reach. Motivated by research work done in the fields
of cognitive systems, visual perception, and psychology of memory we designed and implemented a memory architecture for visual tasks. Structural and functional
concepts of the memory architecture were modeled on the ones found in natural systems. We present an efficient implementation based on parallel programming
techniques. The memory module is integrated into a distributed system for speech and image analysis, which is currently developed in the Sonderforschungsbereich
(SFB) 360, Situated Artificial Communicators, where a hybrid vision system combining neural and semantic networks is used.
