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Title: Emotions and a Prior Knowledge Representation in Artificial General Intelligence
Authors: Gavrilov, Andrey
Keywords: Emotions
Neural Networks
Knowledge Representation
Hybrid Intelligent Systems
Artificial Intelligence
Cognitive Simulation
Issue Date: 2008
Publisher: Institute of Information Theories and Applications FOI ITHEA
Abstract: In this paper a prior knowledge representation for Artificial General Intelligence is proposed based on fuzzy rules using linguistic variables. These linguistic variables may be produced by neural network. Rules may be used for generation of basic emotions – positive and negative, which influence on planning and execution of behavior. The representation of Three Laws of Robotics as such prior knowledge is suggested as highest level of motivation in AGI.
ISSN: 1313-0455
Appears in Collections:Book 5 Intelligent Technologies and Applications

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