An empathy learning problem for HSI: To be empathic, self-improving and ambient

Empathy is a learnable skill that requires experiential learning and practice of empathic ability for it to improve and mature. In the context of human-system interaction (HSI) this can mean that a system should be permitted to have an initial knowledge of empathy provision that is inaccurate or incomplete, but with this knowledge evolving and progressing over time through learning from experience. This problem has yet to be defined and dealt in HSI. This paper is an attempt to state an empathy learning problem for an ambient intelligent system to self-improve its empathic responses based on user affective states.

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