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Found 3 papers, 2 papers with code
Class Teaching for Inverse Reinforcement Learners
In this paper we propose the first machine teaching algorithm for multiple inverse reinforcement learners.
Explainable Agency by Revealing Suboptimality in Child-Robot Learning Scenarios
In the application scenario, the child and the robot learn together how to play a zero-sum game that requires logical and mathematical thinking.
Perceive, Represent, Generate: Translating Multimodal Information to Robotic Motion Trajectories
We present Perceive-Represent-Generate (PRG), a novel three-stage framework that maps perceptual information of different modalities (e. g., visual or sound), corresponding to a sequence of instructions, to an adequate sequence of movements to be executed by a robot.
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