Using theories of behaviour change, argumentation theory, and findings in social psychology, our research explores new methods to raise the persuasiveness of adaptive dialog-based systems using tailored arguments and onscreen characters to enhance the system's credibility and trustworthiness. Initial results revealed the existence of individual preferences for arguments, types of communication, and appearance of onscreen characters. In the future, we will explore methods to learn these preferences through interactions with the user, and to utilize them to maximize the persuasion effect of the system. The final outcome of the research will be a persuasion model that is capable of modelling the user's cognitive and affective state and generating tailored arguments to move the user in the desired direction.
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