2. An online learning dialog method implemented at a computing device, the method comprising: receiving, at the computing device, voice input from a user; determining, at the computing device, whether the voice input from the user is accepted as understood and initiate corresponding actions or the voice input is ambiguous and is in need of exploration based at least on a probability distribution associated with uncertainty regarding parameters of a decision engine model applied to the voice input, wherein the probability distribution is defined by an influence diagram that is configured to apply the Thompson strategy; selecting an action based, at least in part, upon the probability distribution; receiving, at the computing device, feedback associated with the selected action; and updating at least one of the parameters of the decision engine model based, at least in part, upon the feedback associated with the selected action such that the decision engine model of the computing device is configured to maximize long term expected utility via the updating at least the one of the parameters of the decision engine model, wherein the feedback comprises a lack of verbal response to the selected action in a threshold period of time.
2. An online learning dialog method implemented at a computing device, the method comprising: receiving, at the computing device, voice input from a user; determining, at the computing device, whether the voice input from the user is accepted as understood and initiate corresponding actions or the voice input is ambiguous and is in need of exploration based at least on a probability distribution associated with uncertainty regarding parameters of a decision engine model applied to the voice input, wherein the probability distribution is defined by an influence diagram that is configured to apply the Thompson strategy; selecting an action based, at least in part, upon the probability distribution; receiving, at the computing device, feedback associated with the selected action; and updating at least one of the parameters of the decision engine model based, at least in part, upon the feedback associated with the selected action such that the decision engine model of the computing device is configured to maximize long term expected utility via the updating at least the one of the parameters of the decision engine model, wherein the feedback comprises a lack of verbal response to the selected action in a threshold period of time. 16. A voice-controlled web browser embedded on a non-transitory computer storage medium to implement the method as recited in claim 2 .