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A Multilayer Architecture for Cognitive Systems

Authors:
Veronika Thurner
Thorsten Gressling

Keywords: Cognitive system; Multilayer architecture; Technical work place; Machine learning; Context sensitive; Neural network.

Abstract:
Many technical work places, such as laboratories or test beds, are the setting for well-defined processes requiring both high precision and extensive documentation, to ensure accuracy and support accountability that often is required by law, science, or both. In this type of scenario, it is desirable to delegate certain routine tasks, such as documentation or preparatory next steps, to some sort of automated assistant, in order to increase precision and reduce the required amount of manual labor in one fell swoop. At the same time, this automated assistant should be able to interact adequately with the human worker, to ensure that the human worker receives exactly the kind of support that is required in a certain context. To achieve this, we introduce a multilayer architecture for cognitive systems that structures the system's computation and reasoning across well-defined levels of abstraction, from mass signal processing up to organization-wide, intention-driven reasoning. By partitioning the architecture into well-defined, distinct layers, we reduce complexity and thus facilitate both the implementation and the training of the cognitive system. On this basis, we outline the functional modules of a cognitive system supporting the execution of partially manual processes in technical work places.

Pages: 63 to 71

Copyright: Copyright (c) IARIA, 2018

Publication date: February 18, 2018

Published in: conference

ISSN: 2308-4197

ISBN: 978-1-61208-609-5

Location: Barcelona, Spain

Dates: from February 18, 2018 to February 22, 2018