Configuration of dialogue agent with multiple knowledge sources

Knowledge base is a key component of a dialogue agent which determines its usability, performance as well as intelligence. Usually one type of knowledge source is tailored towards specific application or task. One challenge for developing multiple-domain dialogue agents is how to represent the domain knowledge in their respective ways for the best efficiency and easy construction of queries from natural language. There are a variety of knowledge sources available for building up dialogue agents such as relational database, ontology, knowledge base (KB), search index, artificial intelligence markup language (AIML) and the World Wide Web, etc. In this paper, we present a systematic way of configuring dialogue agents supported by multiple knowledge sources. With the proposed dialogue framework, we provide a complete solution for the development of various dialogue systems with the support of different dialogue management techniques, multiple protocols for cloud-enabled dialogue services, pluggable infrastructure for component reuse and service enhancement, strong scripting functions in both XML and Python. We have constructed various dialogue agents with this framework. Results show that these agents are robust and the development cycle can be considerably reduced.