Abstract

Advances in psychology have revealed that emotions and rationality are interlinked and emotions are essential for rational behaviour and decision making. Therefore, integration of emotions with intelligent systems has become an important topic in engineering. The integration of emotions into intelligent systems requires computational models to generate emotions from external and internal sources. This paper first provides a survey of current computational models of emotion and their applications in engineering. Finally, it assesses potential of integrating emotions in wireless sensor networks (WSNs) by listing some use scenarios and by giving one model application. In this model application performance of a neural network for event detection has been improved using brain emotional learning based intelligent controller (BELBIC).

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