Spiking Reflective Processing Model for Stress-Inspired Adaptive Robot Partner Applications

Spiking Reflective Processing Model for Stress-Inspired Adaptive Robot Partner Applications

Tiong Yew Tang (Tunku Abdul Rahman University College, Malaysia), Simon Egerton (La Trobe University, Australia) and János Botzheim (Tokyo Metropolitan University, Japan)
Copyright: © 2019 |Pages: 20
DOI: 10.4018/978-1-5225-8060-7.ch049
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In a real-world environment, a social robot is constantly required to make many critical decisions in an ambiguous and demanding (stressful) environment. Hence, a biological stress response system model is a good gauge indicator to judge when the robot should react to such environment and adapt itself towards the environment changes. This work is to implement the Smerek's reflective processing model into human-robot communication application where reflective processing is triggered during such situations where the best action is not known. The authors want to investigate how to address better the human-robot communication problems with the focus on reflective processing model in the perspectives of working memory, Spiking Neural Network (SNN) and stress response system. The authors had applied their proposed Spiking Reflective Processing model for the human-robot communication application in a university population. The initial experimental results showed the positive attitude changes before and after the human-robot interaction experiment.
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Literature Review

Biological Stress Response System and Working Memory

In related cognitive psychology research work, Lupien et al. (Lupien et al., 2002) experimented young male test subjects for working memory on a list of 12 words with different doses of glucocorticoids (cortisol or stress hormone). In her experimental results, a working memory retrieval performance against the level of glucocorticoids had exhibited and discovered the inverted-U-shape phenomenon. Such phenomenon is similar to the phenomenon as described by Yerkes and Dodson (Dodson, 1915).

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