14. In combination, a system for generating dialogs for learning a dialog policy and a computer-implemented dialog system, the system for generating dialogs comprising: memory which stores a dialog tree for each of a plurality of scenarios, wherein paths through the tree correspond to respective dialogs and nodes of the tree each represent a turn of a dialog, whereby some of the nodes correspond to user annotations and others of the nodes correspond to agent annotations; a tree update component for updating the dialog trees based on annotations of annotators in a pool of annotators serving as virtual agents and users; a reactive tree expansion component which progressively expands the dialog trees by repeated selection of a next node to be annotated by one of the annotators in the pool, the next node being selected based on a respective computed measure of uncertainty for each of the current nodes in one of the dialog trees, whereby when the next node corresponds to a user annotation, a text annotation is provided by the selected annotator for the next node, and when the next node corresponds to an agent annotation, a dialog act is selected by the selected annotator for the node; a dialog corpus generator which generates a corpus of dialogs from the expanded dialog trees; a dialog policy learning component which learns a dialog policy based on the corpus of dialogs, the learning of the dialog policy including learning a classifier model which predicts a next action for a current state of a dialog; and a processor which implements the tree update component, reactive tree expansion component, and dialog corpus generator; the dialog system being configured for conducting a dialog between a virtual agent and a user, in which the learned dialog policy predicts, based on a state of the dialog, a next action to perform, the action being converted, by the dialog system, to a next utterance of the virtual agent.
14. In combination, a system for generating dialogs for learning a dialog policy and a computer-implemented dialog system, the system for generating dialogs comprising: memory which stores a dialog tree for each of a plurality of scenarios, wherein paths through the tree correspond to respective dialogs and nodes of the tree each represent a turn of a dialog, whereby some of the nodes correspond to user annotations and others of the nodes correspond to agent annotations; a tree update component for updating the dialog trees based on annotations of annotators in a pool of annotators serving as virtual agents and users; a reactive tree expansion component which progressively expands the dialog trees by repeated selection of a next node to be annotated by one of the annotators in the pool, the next node being selected based on a respective computed measure of uncertainty for each of the current nodes in one of the dialog trees, whereby when the next node corresponds to a user annotation, a text annotation is provided by the selected annotator for the next node, and when the next node corresponds to an agent annotation, a dialog act is selected by the selected annotator for the node; a dialog corpus generator which generates a corpus of dialogs from the expanded dialog trees; a dialog policy learning component which learns a dialog policy based on the corpus of dialogs, the learning of the dialog policy including learning a classifier model which predicts a next action for a current state of a dialog; and a processor which implements the tree update component, reactive tree expansion component, and dialog corpus generator; the dialog system being configured for conducting a dialog between a virtual agent and a user, in which the learned dialog policy predicts, based on a state of the dialog, a next action to perform, the action being converted, by the dialog system, to a next utterance of the virtual agent. 16. The system of claim 14 , further comprising at least one of: a dialog policy refinement component which refines the learned dialog policy; and an output component which outputs at least one of: the corpus of dialogs; and a dialog policy generated based on the corpus of dialogs.