Conversational agents have been widely adopted in dialogue systems for various business
purposes. Many existing conversational agents are rule-based and require significant
human intervention to adapt the knowledge and conversational flow. In this paper, we
propose a graph-based adaptive conversational agent model which is capable of learning
knowledge from human beings and adapting the knowledge-base according to human-
agent interactions. Studies to evaluate the proposed model are conducted and presented …

Conversational agents have been widely adopted in dialogue systems for various business
purposes. Many existing conversational agents are rule-based and require significant
human intervention to adapt the knowledge and conversational flow. In this thesis, I propose
a graph-based adaptive conversational agent model which is capable of learning
knowledge from human beings and adapting the knowledge-base according to user-agent
interactions. Extensive experiments have been conducted to evaluate the proposed model …