{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,19]],"date-time":"2025-03-19T14:44:23Z","timestamp":1742395463683},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643684369","type":"print"},{"value":"9781643684376","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,9,28]],"date-time":"2023-09-28T00:00:00Z","timestamp":1695859200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,9,28]]},"abstract":"<jats:p>Implicit imitation assumes that learning agents observe only the state transitions of an agent they use as a mentor, and try to recreate them based on their own abilities and knowledge of their environment. In this paper, we put forward a deep implicit imitation Q-network (DIIQN) model, which incorporates ideas from three well-known Deep Q-Network (DQN) variants. As such, we enable a novel implicit imitation method for online, model-free deep reinforcement learning. Our thorough experimentation in the complex environment of the emerging lane-free traffic paradigm, verifies the benefits of our approach. Specifically, we show that deep implicit imitation RL dramatically accelerates the learning process when compared to a \u201cvanilla\u201d DQN method; and, unlike explicit imitation reinforcement learning, it is able to outperform mentor performance without resorting to additional information, such as the mentor\u2019s actions.<\/jats:p>","DOI":"10.3233\/faia230304","type":"book-chapter","created":{"date-parts":[[2023,9,29]],"date-time":"2023-09-29T09:03:14Z","timestamp":1695978194000},"source":"Crossref","is-referenced-by-count":2,"title":["Deep Reinforcement Learning with Implicit Imitation for Lane-Free Autonomous Driving"],"prefix":"10.3233","author":[{"given":"Iason","family":"Chrysomallis","sequence":"first","affiliation":[{"name":"Technical University of Crete, Chania, Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dimitrios","family":"Troullinos","sequence":"additional","affiliation":[{"name":"Technical University of Crete, Chania, Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Georgios","family":"Chalkiadakis","sequence":"additional","affiliation":[{"name":"Technical University of Crete, Chania, Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ioannis","family":"Papamichail","sequence":"additional","affiliation":[{"name":"Technical University of Crete, Chania, Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Markos","family":"Papageorgiou","sequence":"additional","affiliation":[{"name":"Technical University of Crete, Chania, Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","ECAI 2023"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA230304","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,29]],"date-time":"2023-09-29T09:03:16Z","timestamp":1695978196000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA230304"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9,28]]},"ISBN":["9781643684369","9781643684376"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia230304","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,9,28]]}}}