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As hybrid interactions between humans and artificial agents become more prevalent, social skills are increasingly essential for autonomous systems. Beyond assisting in various tasks, robots are expected to understand human states and recognize that knowledge and perceptions of the world can differ, influencing overall behavior. This ability is closely tied to motivation, which plays a crucial role in driving autonomous agents’ actions. In this work, we explore the interaction between two intrinsically motivated cognitive autonomous robots with distinct profiles and preferences, utilizing Theory of Mind to infer each other’s motivations. We investigate the conditions under which they successfully collaborate to achieve mutual well-being and the circumstances that hinder cooperation. Our findings indicate that successful interactions emerge when at least one agent prioritizes helping others and when their profiles are aligned, leading to positive outcomes for both.
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Berto et al. (2025) studied this question.
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