{"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/towards-learning-transferable-conversational","title":"Towards Learning Transferable Conversational Skills using Multi-dimensional Dialogue Modelling","arxiv_id":"1804.00146","date":"2018-03-31","proceeding":null,"authors":["Simon Keizer","Verena Rieser"],"abstract":"Recent statistical approaches have improved the robustness and scalability of\nspoken dialogue systems. However, despite recent progress in domain adaptation,\ntheir reliance on in-domain data still limits their cross-domain scalability.\nIn this paper, we argue that this problem can be addressed by extending current\nmodels to reflect and exploit the multi-dimensional nature of human dialogue.\nWe present our multi-dimensional, statistical dialogue management framework, in\nwhich transferable conversational skills can be learnt by separating out\ndomain-independent dimensions of communication and using multi-agent\nreinforcement learning. Our initial experiments with a simulated user show that\nwe can speed up the learning process by transferring learnt policies.","url_abs":"http://arxiv.org/abs/1804.00146v1","url_pdf":"http://arxiv.org/pdf/1804.00146v1.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":"towards-learning-transferable-conversational","repo_url":"https://bitbucket.org/skeizer/madrigal","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"dialogue-management","task_name":"Dialogue Management"},{"task_slug":"domain-adaptation","task_name":"Domain Adaptation"},{"task_slug":"management","task_name":"Management"},{"task_slug":"multi-agent-reinforcement-learning","task_name":"Multi-agent Reinforcement Learning"},{"task_slug":"reinforcement-learning","task_name":"Reinforcement Learning"},{"task_slug":"reinforcement-learning-1","task_name":"Reinforcement Learning (RL)"},{"task_slug":"spoken-dialogue-systems","task_name":"Spoken Dialogue Systems"},{"task_slug":"reinforcement-learning-2","task_name":"reinforcement-learning"}],"methods":[{"method_slug":"speed","method_name":"SPEED"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}