A proposal for adapting robot behaviours using fuzzy Q-learning in cognitive serious game scenarios

The repetitive and monotonous character of cognitive training may lead to waning interest and eventual disengagement among older adults with cognitive impairments. To address this issue, this study proposes an adaptive approach wherein a Socially Assistive Robot (SAR) autonomously selects optimal actions to sustain an emotional state in older adults while participating in serious cognitive training games. The aim is to propose an adaptation strategy that leverages fuzzy Q-learning to prompt users to maintain a positive state.