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Personal identity module using psychoevolutionary emotion theory for social robots

机译:个人身份模块使用精神辩护情感理论为社会机器人理论

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Robots that interacts socially in human being environment should be able to understand and act over it using clues from humans; it includes all types of expression: facial, non-facial, verbal and nonverbal affective expressions. These behaviors need a model capable to compute external and internal information to construct autonomous robots. In this paper, we are proposing a basis for modeling some reflexes inherent to human beings that are responsible by personal identity of each individual. The proposed model is constituted by two reflex modules and an emotion module that are based on psychoevolutionary theory. Then, this model has been inserted in our social architecture as an improvement of old motivational module and evaluated in a simulator. The advantage of the proposed approach from others is the possibility of representing the emotion as an internal function which varies over the time with different types of interaction. The experimental results show that this module is capable to emulate adequately human beings basic reflex in a robot during a simple interaction with a caregiver.
机译:社会在人类环境中互动的机器人应该能够使用人类的线索来理解和行动;它包括所有类型的表达:面部,非面部,口头和非语言情感表达。这些行为需要一个模型,能够计算外部和内部信息来构建自主机器人。在本文中,我们提出了对人类固有的一些反射的依据,这些反应是由每个人的个人身份负责的人。所提出的模型由两个反射模块和基于心理学理论的情感模块构成。然后,该模型已在我们的社交架构中插入作为旧动机模块的改进,并在模拟器中进行评估。所提出的方法的优点是从其他方面的优点是将情绪作为内部功能表示,这在具有不同类型的交互的时间内变化。实验结果表明,在与护理人员的简单互动中,该模块能够在机器人中充分模拟人类基本反射。

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