{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,10]],"date-time":"2026-01-10T22:22:51Z","timestamp":1768083771997,"version":"3.49.0"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,8]]},"abstract":"<jats:p>Reinforcement learning agents can learn to solve sequential decision tasks by interacting with the environment. Human knowledge of how to solve these tasks can be incorporated using imitation learning, where the agent learns to imitate human demonstrated decisions. However, human guidance is not limited to the demonstrations. Other types of guidance could be more suitable for certain tasks and require less human effort. This survey provides a high-level overview of five recent learning frameworks that primarily rely on human guidance other than conventional, step-by-step action demonstrations. We review the motivation, assumption, and implementation of each framework. We then discuss possible future research directions.<\/jats:p>","DOI":"10.24963\/ijcai.2019\/884","type":"proceedings-article","created":{"date-parts":[[2019,7,28]],"date-time":"2019-07-28T07:46:05Z","timestamp":1564299965000},"page":"6339-6346","source":"Crossref","is-referenced-by-count":39,"title":["Leveraging Human Guidance for Deep Reinforcement Learning Tasks"],"prefix":"10.24963","author":[{"given":"Ruohan","family":"Zhang","sequence":"first","affiliation":[{"name":"Department of Computer Science, University of Texas at Austin, USA"}]},{"given":"Faraz","family":"Torabi","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Texas at Austin, USA"}]},{"given":"Lin","family":"Guan","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Texas at Austin, USA"}]},{"given":"Dana H.","family":"Ballard","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Texas at Austin, USA"}]},{"given":"Peter","family":"Stone","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Texas at Austin, USA"}]}],"member":"10584","event":{"name":"Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}","theme":"Artificial Intelligence","location":"Macao, China","acronym":"IJCAI-2019","number":"28","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"start":{"date-parts":[[2019,8,10]]},"end":{"date-parts":[[2019,8,16]]}},"container-title":["Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2019,7,28]],"date-time":"2019-07-28T07:52:27Z","timestamp":1564300347000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2019\/884"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2019,8]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2019\/884","relation":{},"subject":[],"published":{"date-parts":[[2019,8]]}}}