An Affective Robot Companion for Assisting the Elderly in a Cognitive Game Scenario
Being able to recognize emotions in human users is considered a highly desirable trait in Human-Robot Interaction (HRI) scenarios. However, most contemporary approaches rarely attempt to apply recognized emotional features in an active manner to modulate robot decision-making and dialogue for the benefit of the user. In this position paper, we propose a method of incorporating recognized emotions into a Reinforcement Learning (RL) based dialogue management module that adapts its dialogue responses in order to attempt to make cognitive training tasks, like the 2048 Puzzle Game, more enjoyable for the users.
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Decision MakingDialogue ManagementManagementPlaying the Game of 2048Positionreinforcement-learningReinforcement Learning (RL)Similar Papers 제목 키워드 기반
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