Taking decisions in a Hybrid Conversational AI architecture using Influence Diagrams

This paper explores the application of the Influence Diagrams model for decision-making in the context of conversational agents. The system consists of a Conversational Recommender System (CoRS), in which the decision-making module is separate from the language generation module. It provides the capability to evolve a belief based on user responses, which in turn influences the decisions made by the conversational agent. The proposed system is based on a pre-existing CoRS that relies on Bayesian Networks informing a separate decision process. The introduction of Influence Diagrams aims to integrate both Bayesian inference and the dialogue move selection phase into a single model, thereby generalising the decision-making process. To test the effectiveness and plausibility of the dialogues generated by the developed CoRS, a dialogue simulator was created and the simulated interactions were evaluated by a pool of human judges.