Positing A Growth-Centric Learning of Empathy Models in HSI

抄録

This paper attempts to define an operable empathy learning problem for an ambient intelligent system in light of the user modeling and adaptive user-interfaces problems that will motivate an efficiency-centric implementation, i.e., the system must improve its ambient responses on its own online in an adaptive and optimal way based on its knowledge of user affects and ambient contexts. It is to our knowledge that this problem has yet to be defined and dealt with in the context of human-system interactions.