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We propose a framework for an agent that can infer, during the interaction, a level of trust from human behavior and adapt its behavior accordingly. To achieve this, we propose reframing the problem as an Ad Hoc Teamwork (AHT) problem and solving it with a type-based method that uses a library of teammates’ models and trains the agent to adapt to different types of teammates. We plan to implement this adaptive behavior and analyse its impact in a human-agent collaboration scenario. 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