Abstract: The present invention is a masterbot architecture in a scalable multi-service virtual assistant platform that can construct a fluid and dynamic dialogue by assembling responses to end user utterances from two kinds of agents, information agents and action agents. A plurality of information agents obtain at least one information value from a parsed user input and/or contextual data. A plurality of action agents perform one or more actions in response to the parsed user input, the contextual data, and/or the information value. A masterbot arbitrates an activation of the plurality of information agents and the plurality of action agents. The masterbot comprises access to a machine-learning module to select an appropriate action agent, where one or more information agents are activated based on the selected appropriate action agent.

Abstract: The present invention is a masterbot architecture in a scalable multi-service virtual assistant platform that can construct a fluid and dynamic dialogue by assembling responses to end user utterances from two kinds of agents, information agents and action agents. A plurality of information agents obtain at least one information value from a parsed user input and/or contextual data. A plurality of action agents perform one or more actions in response to the parsed user input, the contextual data, and/or the information value. A masterbot arbitrates an activation of the plurality of information agents and the plurality of action agents. The masterbot comprises an action agent selector module to select an appropriate action agent; a prerequisite validator module to validate that one or more prerequisite conditions of the selected action agent have been met; and an action invocation module to perform one or more selected actions of the selected action agent.

Abstract: The present invention is an action agent architecture in a scalable multi-service virtual assistant platform that can construct a fluid and dynamic dialogue by assembling responses to end user utterances from two kinds of agents, information agents and action agents. A plurality of information agents obtain at least one information value from a parsed user input and/or contextual data. A plurality of action agents perform one or more actions in response to the parsed user input, the contextual data, and/or an information value obtained from at least one of the information agents. The plurality of action agents are created through a declarative language by specifying one or more triggering conditions, one or more action invocation parameters, one or more information agents as pre-requisites, and one or more responses. A natural language generation (NLG) module renders a response back to the user after the one or more actions are performed.

Abstract: The present invention is a scalable multi-service virtual assistant platform that can construct a fluid and dynamic dialogue by assembling responses to end user utterances from two kinds of agents, information agents and action agents. The information agents and action agents are managed by a masterbot or arbiter. The virtual assistant can gain new skills by getting instructions about a new service expressed in a form of pre-requisites and action combinations; the virtual assistant platform automatically handles dialogue generation, arbitration and optimization to survey prerequisites from the end user, and eventually to take action. The present invention allows a large number of services to implemented using a small number of building blocks. These building blocks can be used to assemble a much larger number of services. In turn, each service can be delivered through a large variety of conversations with end users, enabling a fluid and dynamic dialogue to be seamlessly implemented.