The Chef's Hat Simulation Environment for Reinforcement-Learning-Based Agents

• URL: http://arxiv.org/abs/2003.05861v1
• Date: Thu, 12 Mar 2020 15:52:49 GMT
• Title: The Chef's Hat Simulation Environment for Reinforcement-Learning-Based Agents
• Authors: Pablo Barros, Anne C. Bloem, Inge M. Hootsmans, Lena M. Opheij, Romain H.A. Toebosch, Emilia Barakova and Alessandra Sciutti
• Abstract summary: We propose a virtual simulation environment that implements the Chef's Hat card game, designed to be used in Human-Robot Interaction scenarios. This paper provides a controllable and reproducible scenario for reinforcement-learning algorithms.
• Score: 54.63186041942257
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: To achieve social interactions within Human-Robot Interaction (HRI) environments is a very challenging task. Most of the current research focuses on Wizard-of-Oz approaches, which neglect the recent development of intelligent robots. On the other hand, real-world scenarios usually do not provide the necessary control and reproducibility which are needed for learning algorithms. In this paper, we propose a virtual simulation environment that implements the Chef's Hat card game, designed to be used in HRI scenarios, to provide a controllable and reproducible scenario for reinforcement-learning algorithms.

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