Creating a general collaborative dialogue agent with lounge strategy feature
In this paper, we focus on an agent-based architecture for task-oriented dialogue management. We present our deliberation process based on optimizing the length of a dialogue in terms of its turns needed to accomplish a task. As innovative features, the manager accommodates a lounge strategy for passing initiative back to the user, and a two-layered structure for dialogue context representation. We show that applying the lounge strategy during a dialogue leads to improving the information exchange rate by approximately 5% compared to common dialogue strategies alternative. Furthermore, we present two of our dialogues and analyze them with respect to the agent description. At the end of the paper, we suggest future extensions and modifications to the architecture, and conclude.
agent-based dialogue management system adaptability dialogue systems artificial intelligence