Foundations for a theory of mind for a humanoid robot
Foundations for a theory of mind for a humanoid robot
Theory of mind (ToM) on robots: a functional neuroimaging study
Proceedings of the 3rd ACM/IEEE international conference on Human robot interaction
Toward Logic-Based Cognitively Robust Synthetic Characters in Digital Environments
Proceedings of the 2008 conference on Artificial General Intelligence 2008: Proceedings of the First AGI Conference
PsychSim: modeling theory of mind with decision-theoretic agents
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Towards a simple robotic theory of mind
PerMIS '09 Proceedings of the 9th Workshop on Performance Metrics for Intelligent Systems
Corpus-based intention recognition in cooperation dilemmas
Artificial Life
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The psychology term Theory of Mind (ToM) refers to the ability of an agent to recognize that an observed actor acts according to intentions and plans. In humans and some primates, ToM is fundamental to effective cooperation and competition, and is a key component of high-level cognition. In this paper, we explore the use of evolutionary robotics methods to create a robotic ToM. We use a co-evolutionary setup to evolve controllers that retrospectively explain an observed actor's behavior, and new actions that elicit new and more revealing behaviors. Evolved controllers can then be used to predict, manipulate and exploit the observed actor's behavior for cooperation or competition. Experimental results are shown in a physically-realistic simulation environment, and demonstrate an significant performance improvement compared to a direct estimation baseline.