Matching artificial agents' and users' personalities: designing agents with regulatory-focus and testing the regulatory fit effect

This work endow artificial agents with regulatory focus, taking a sociocognitive approach of personality, by using machine-learning techniques to test whether this personality can be perceived by users and if there is a regulatory fit effect on the users credibility judgement of the agent.