Emotion and memory model for social robots: a reinforcement learning based behaviour selection

Emotion-Based Reinforcement Learning

Studies have shown that counterfactual reasoning can shape human decisions. However, there is a gap in the literature between counterfactual choices in description-based and experience-based paradigms. While studies using descriptionbased paradigms suggest participants maximize expected subjective emotion, studies using experience-based paradigms assume that participants learn the values of opt...

Behaviour-Based Reinforcement Learning

Although behaviour-based robotics has been successfully used to develop autonomous mobile robots up to a certain point, further progress may require the integration of a learning model into the behaviour-based framework. Reinforcement learning is a natural candidate for this because it seems well suited to the problems faced by autonomous agents. However, previous attempts to use reinforcement ...

Emotion-based Architecture for Social Interactive Robots

Abstraction Selection in Model-based Reinforcement Learning

ion Selection in Model-Based Reinforcement Learning Nan Jiang, Alex Kulesza, Satinder Singh {NANJIANG,KULESZA,BAVEJA}@UMICH.EDU Computer Science & Engineering, University of Michigan

RUNNING HEAD: Social cognition and reinforcement learning Social cognition as reinforcement learning: Feedback modulates emotion inference

Neuroscientific studies of social cognition typically employ paradigms in which perceivers draw single-shot inferences about the internal states of strangers. Real world social inference features much different parameters: people often encounter and learn about particular social targets (e.g., friends) over time and receive feedback about when their inferences are correct or incorrect. Here we ...