{"id":1158,"date":"2019-03-11T09:26:48","date_gmt":"2019-03-11T09:26:48","guid":{"rendered":"https:\/\/www.mub.eps.manchester.ac.uk\/in-abstract\/?p=1158"},"modified":"2019-09-16T14:36:04","modified_gmt":"2019-09-16T13:36:04","slug":"would-a-robot-trust-you-developmental-robotics-model-of-trust-and-theory-of-mind","status":"publish","type":"post","link":"https:\/\/www.mub.eps.manchester.ac.uk\/in-abstract\/would-a-robot-trust-you-developmental-robotics-model-of-trust-and-theory-of-mind\/","title":{"rendered":"Would a robot trust you? Developmental robotics model of trust and theory of mind"},"content":{"rendered":"

A robotics model of trust and theory of mind<\/strong><\/p>\n

Researchers from the School of Computer Science at the University of Manchester have developed a novel computation model of Theory of Mind to support trust in human-robot interaction. Various studies have examined how trust is attributed by people to robots, but there are no current models that investigate the opposite scenario, where a robot is the trustor and a human is the trustee. This research proposes an artificial cognitive architecture based on the developmental robotics paradigm that can estimate the trustworthiness of its human interactors for the purpose of decision making. This is accomplished using Theory of Mind, the psychological ability to assign to others beliefs and intentions that can differ from one\u2019s owns. The novel ognitive architecture integrates a probabilistic Theory of Mind and trust model supported by an episodic memory system. The architecture was tested using developmental psychological experimental paradigms, and results demonstrate a new method to enhance the quality of human and robot collaborations. This work will allow autonomous robots to evaluate the trustworthiness of its sources of information for joint task scenarios where people and robots must collaborate to reach shared goals.<\/p>\n

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