Cloud Interconnected Affect Reward based Automation Ambient Comfort Controller
Keywords: Ambient intelligence, automatic control, emotion recognition, human computer interaction, machine learning
AbstractThe paper presents the human Affect Reward Based Automation Ambient Comfort Controller (ACARBC) as the interconnected cloud computing intelligent services that provide intelligent calculus for any instrumented interconnected environment sense and control system. The ACARBC has been modelled and, as the experimental results show, that an environmental state characteristics that create an optimum ambient comfort can be obtained by ACAR index. The ACAR index is dependent on human physiological parameters: the temperature, the ECG- electrocardiogram and the EDA-electro-dermal activity. The fuzzy logic is used to approximate the ACAR index function by defining two fuzzy inference systems: the Arousal-Valence System, and the Ambient Comfort Affect Reward (ACAR) System. The Radial Basis Neural Network is used as the main component of the ACARBC to performing of two roles - the policy structure, known as the Actor, used to select actions, and the estimated value function, known as the Critic that criticizes the actions made by the Actor. The Critic in this paper was used as a value function approximation of the continuous learning tasks of the ACARBC.
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