Dynamic selection of virtual agents in a mutli-domain expert system

摘要

An expert system incorporates multiple virtual-agent experts, each trained in a particular field or domain. When a user enters a block of input, an interactive front-end infers the semantic meaning of the input and creates a chat-table record that stores the inferred meaning and other characteristics of the input. A distributed virtual-assistant manager (DVAM) module uses that record to identify the domain of the input and, after retrieving cross-reference information stored in a virtual-assistant intent (VAI) table, selects a virtual-agent expert trained in the identified domain. If necessary, the DVAM directs the front-end to seamlessly switch the user to the newly selected expert. As the session continues, the system continues to dynamically switch the user to different experts as the session traverses different domains. The system may also consider the domain history of the entire session when selecting a domain.