Proposals for strategies for dialogical argumentation often focus on situations where one of the agents wins the dialogue and the other agent loses. Yet in real-world argumentation, it is common for agents to not view a dialogue as a zero-sum game. Rather, the agents may enter into a dialogue with divergent but not diametrically opposing views on what is important (e.g. a doctor trying to persuade a patient to give up smoking when the patient would like to be healthy but gets some pleasure from smoking). Furthermore, there may be multiple persuasion goals (e.g. reduce smoking of cigarettes to 20 per day, or 10 per day, or 5 per day, or 1 per day, or 0 per day, where the doctor prefers 0 per day most, and 20 per day least, whereas the patient might prefer 5 per day most, and 20 per day and 0 per day least). In order to develop persuasive chatbots that support this kind of behaviour change application, this paper presents dialogue protocols, and a strategy for a chatbot, to optimize choice of moves.