This paper describes an approach for guiding human choice-making by a computerized agent, in a conversational setting, where both user and agent provide meaningful input. In the proposed approach, the agent attempts to convince a person by providing examples for the person to emulate or by providing justifications for the person to internalize and build or change her preferences accordingly. The agent can take into account examples and justifications provided by the person. In a series of experiments where the task was selecting a location for a school, a computer agent interacted with subjects using a textual chat-type interface, with different agent designs being used in different experiments. The results show that the example-providing agent outperformed the justification providing agent and both, surprisingly, outperformed an agent which presented the subject with both examples and justifications. In addition, it was demonstrated that in some cases the best strategy for the agent is to keep silent.
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