Enhancing Companion Dialogue with Episodic Memory

Artificial Companions are computer systems that interact and collaborate with the user over a longer period of time, employing human-like communication. They have memory and are able to learn from the interaction with their users. Due to their long-term relationships with users and their ability to communicate in a human-like fashion they have social effects on the user. We aim at improving the dialogue capabilities of companions by endowing them with episodic memory (EM) and integrating it with action selection and dialogue control. Our research builds upon the platform and companions developed in the RASCALLI project [1][2], but can be easily transferred to other applications. Goals The goal of equipping companions with EM is to achieve more coherent, believable behaviour based on experiences: ● support action selection based on similarity to past experiences ● explain actions of companions (mistakes / offline tasks) ● provide more interesting dialogue by being able to make statements about: ● users ' current and past preferences, and their relation to the current situation ● patterns, similarities and dissimilarities between current and past interactions ● employ user preferences stored in the EM to: ● improve answer retrieval from knowledge bases ● proactively present interesting information to the use