A procedure for automatic adaptation to the user in intelligent virtual agents
Paper i proceeding, 2019
This paper describes procedures for improving the functionality of task-oriented intelligent virtual agents (IVAs) and carrying out adaptation to the user in such agents. The functionality improvement is based on automatic extension of input patterns (rules), using a database of interchangeable phrases. This extension results in greater flexibility both regarding the users input and the agents output. The adaptation to the user relies on a complexity measure, allowing the agent to assess the level of complexity of the users input and thus to adapt the complexity level of its response. For the case of a simple travel information agent, the pattern extension procedure resulted in an increase in the number of available patterns of around a factor 20, greatly enhancing the agents capacity of adapting its output to the user.
intelligent virtual agents