Stress-inspired dynamic optimisation on working memory for cognitive robot social support systems

Abstract

Robot social support systems such as robot partner's game interactions with elderly people are very important in ageing societies. Human-robot interaction can decrease the risk of ageing disease such as dementia and thus improve the overall quality of life for the elderly people. However, in order for the robot partner to have successful game interactions with the elderly people, the robot partners need to be equipped with a certain degree of cognitive intelligence to guess the meaning and context of game interactions. In this paper, we discuss a biological stress-inspired model for the robot's cognitive intelligence with dynamic optimisation on its working memory. We name this novel robot's cognitive framework as Advanced Intelligence Cognitive Optimisation (AICO). AICO is a server framework for computational intensive cognitive processing for the smart phone robot known as iPhonoid. We have conducted physical robot experiments with our proposed iPhonoid AICO framework on Rényi-Ulam guessing game with real human subjects. The experimental results show that the proposed AICO framework successfully increased the robot's guessing performance in the game interactions. At the same time, the robot behaves according to its emotional conditions to make the game play interesting for the elderly people.