Long Term Memory in Conversational Robots

Sammanfattning: This study discusses an implementation of a long term memory in the robot Furhat. The idea was to find a way to prevent identical and very similar questions from being asked several times and to store the information of which questions have already been asked in a document database. The project encompasses tf-idf, as well as a small-scale test with Word2Vec, to find a vector representation of all questions from Furhat’s database and then clustering these questions with the k-means method. The tests resulted in high scores on all the evaluation metrics used, which is promising for implementation into the actual Furhat robot, as well as further research on similar implementations of long term memory functions in chatbots.