Emotions and a Prior Knowledge Representation in Artificial General Intelligence
- Publisher: Institute of Information Theories and Applications FOI ITHEA
Emotions | Neural Networks | Knowledge Representation | Hybrid Intelligent Systems | Artificial Intelligence | Cognitive Simulation
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.