System and method for automatically focusing the attention of a virtual robot interacting with users

A system for automatically focusing the attention of a virtual robot interacting with users in natural language, the system comprising:

• an interface for receiving natural language input from a user, wherein the natural language input includes at least one natural language component;
• and
• a processor comprising a computer usable medium including computer readable program code embodied in said medium for interacting with a user in natural language, said computer readable program code including:
• computer readable program code for defining at least one category associated with actions executable by the processor during interaction with a user;
• computer readable program code for maintaining an attention focus list comprising an ordered list of one or more categories;
• computer readable program code for recognizing at least one natural language component within the natural language input from said user;
• computer readable program code for examining at least one category in the attention focus list to determine whether the at least one natural language component generates a match with the at least one examined category, wherein the order in which categories are examined is influenced by the order of the categories in the attention focus list;
• and
• computer readable program code for re-ordering for the categories of said attention focus list, wherein the new ordering of the categories is influenced by the categories in the attention focus list for which a match is generated.

A computer program product for interacting with a user in natural language, said computer program product comprising:

• computer readable program code for defining at least one category associated with actions executable by the computer program product during interaction with the user;
• computer readable program code for maintaining an attention focus list comprising one or more categories arranged in an order;
• computer readable program code for receiving natural language input from the user;
• computer readable program code for parsing natural language input from the user into at least one natural language component;
• computer readable program code for examining at least one category in the attention focus list to determine whether the at least one natural language component generates a match with the at least one examined category, wherein the order in which categories are examined is influenced by the order of the attention focus list;
• and
• computer readable program code for generating a new order for the categories of the attention focus list, said new order being influenced by the examined categories which generated a match with the at least one natural language component.

A method of automated learning based on interactions with a user in natural language, said method comprising:

• maintaining at least one category comprising at least one script, wherein the at least one script comprises at least one condition associated with one or more actions, wherein if the condition is satisfied, the actions associated with the condition are executed;
• defining a set of labels, wherein each label is associated with a user input sample in natural language;
• extracting a set of candidate features from the user input sample;
• determining a subset of said candidate features which are associated with said example labels;
• and
• generating scripts for the at least one activatable category based on the subset of candidate features.