{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/training-an-interactive-humanoid-robot-using","title":"Training an Interactive Humanoid Robot Using Multimodal Deep Reinforcement Learning","arxiv_id":"1611.08666","date":"2016-11-26","proceeding":null,"authors":["Heriberto Cuayáhuitl","Guillaume Couly","Clément Olalainty"],"abstract":"Training robots to perceive, act and communicate using multiple modalities\nstill represents a challenging problem, particularly if robots are expected to\nlearn efficiently from small sets of example interactions. We describe a\nlearning approach as a step in this direction, where we teach a humanoid robot\nhow to play the game of noughts and crosses. Given that multiple multimodal\nskills can be trained to play this game, we focus our attention to training the\nrobot to perceive the game, and to interact in this game. Our multimodal deep\nreinforcement learning agent perceives multimodal features and exhibits verbal\nand non-verbal actions while playing. Experimental results using simulations\nshow that the robot can learn to win or draw up to 98% of the games. A pilot\ntest of the proposed multimodal system for the targeted game---integrating\nspeech, vision and gestures---reports that reasonable and fluent interactions\ncan be achieved using the proposed approach.","url_abs":"http://arxiv.org/abs/1611.08666v1","url_pdf":"http://arxiv.org/pdf/1611.08666v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"training-an-interactive-humanoid-robot-using","repo_url":"https://github.com/cuayahuitl/SimpleDS","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"GPL-3.0"}}],"tasks":[{"task_slug":"deep-reinforcement-learning","task_name":"Deep Reinforcement Learning"},{"task_slug":"reinforcement-learning","task_name":"Reinforcement Learning"},{"task_slug":"reinforcement-learning-1","task_name":"Reinforcement Learning (RL)"},{"task_slug":"reinforcement-learning-2","task_name":"reinforcement-learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}