Modeling Human Intention in a Live-Feeling Platform
نویسنده
چکیده
This paper presents a Bayesian Network (BN) model of human intention in an entertainment environment. We present a framework for live-feeling communication that allows an intelligent system to reconfigure its action based on user preferences and intention. The user intentions are learned from a training set of model situations and a hierarchical model of soccer game is integrated with the user intention into a single BN. The trained model is tested on a data set gathered from users. The BN model shows an accuracy of up to 85%.
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