{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T16:49:10Z","timestamp":1791391750592,"version":"4.3.3"},"reference-count":15,"publisher":"Maximum Academic Press","issue":"1","license":[{"start":{"date-parts":[[2016,2,11]],"date-time":"2016-02-11T00:00:00Z","timestamp":1455148800000},"content-version":"unspecified","delay-in-days":41,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["The Knowledge Engineering Review"],"published-print":{"date-parts":[[2016,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Reward shaping has been shown to significantly improve an agent\u2019s performance in reinforcement learning. Plan-based reward shaping is a successful approach in which a STRIPS plan is used in order to guide the agent to the optimal behaviour. However, if the provided knowledge is wrong, it has been shown the agent will take longer to learn the optimal policy. Previously, in some cases, it was better to ignore all prior knowledge despite it only being partially incorrect.<\/jats:p>\n                  <jats:p>This paper introduces a novel use of knowledge revision to overcome incorrect domain knowledge when provided to an agent receiving plan-based reward shaping. Empirical results show that an agent using this method can outperform the previous agent receiving plan-based reward shaping without knowledge revision.<\/jats:p>","DOI":"10.1017\/s026988891500017x","type":"journal-article","created":{"date-parts":[[2016,2,11]],"date-time":"2016-02-11T20:33:12Z","timestamp":1455222792000},"page":"31-43","source":"Crossref","is-referenced-by-count":5,"title":["Overcoming incorrect knowledge in plan-based reward shaping"],"prefix":"10.48130","volume":"31","author":[{"given":"Kyriakos","family":"Efthymiadis","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sam","family":"Devlin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel","family":"Kudenko","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"27968","published-online":{"date-parts":[[2016,2,11]]},"reference":[{"key":"S026988891500017X_ref7","doi-asserted-by":"publisher","DOI":"10.1016\/0004-3702(71)90010-5"},{"key":"S026988891500017X_ref12","unstructured":"Ng A. Y. , Harada D. & Russell S. J. 1999. Policy invariance under reward transformations: theory and application to reward shaping. In Proceedings of the 16th International Conference on Machine Learning, 278\u2013287."},{"key":"S026988891500017X_ref3","doi-asserted-by":"crossref","unstructured":"Devlin S. , Grze\u015b M. & Kudenko D. 2011. An empirical study of potential-based reward shaping and advice in complex, multi-agent systems. Advances in Complex Systems.","DOI":"10.1142\/S0219525911002998"},{"key":"S026988891500017X_ref4","unstructured":"Devlin S. & Kudenko D. 2011. Theoretical considerations of potential-based reward shaping for multi-agent systems. In Proceedings of The Tenth Annual International Conference on Autonomous Agents and Multiagent Systems."},{"key":"S026988891500017X_ref5","unstructured":"Devlin S. & Kudenko D. 2012. Dynamic potential-based reward shaping. In Proceedings of The Eleventh Annual International Conference on Autonomous Agents and Multiagent Systems."},{"key":"S026988891500017X_ref14","unstructured":"Randl\u00f8v J. & Alstrom P. 1998. Learning to drive a bicycle using reinforcement learning and shaping. In Proceedings of the 15th International Conference on Machine Learning, 463\u2013471."},{"key":"S026988891500017X_ref1","unstructured":"Asmuth J. , Littman M. & Zinkov R. 2008. Potential-based shaping in model-based reinforcement learning. In Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 604\u2013609."},{"key":"S026988891500017X_ref2","unstructured":"Bertsekas D. P. 2007. Dynamic Programming and Optimal Control (2 Vol Set), 3rd edition. Athena Scientific."},{"key":"S026988891500017X_ref6","doi-asserted-by":"crossref","unstructured":"Efthymiadis K. & Kudenko D. 2013. Using plan-based reward shaping to learn strategies in StarCraft: Brood War. In Computational Intelligence and Games (CIG). IEEE.","DOI":"10.1109\/CIG.2013.6633622"},{"key":"S026988891500017X_ref8","first-page":"1","article-title":"Belief revision: an introduction","volume":"29","author":"G\u00e4rdenfors","year":"1992","journal-title":"Belief Revision"},{"key":"S026988891500017X_ref9","unstructured":"Grze\u015b M. & Kudenko D. 2008a. Multigrid reinforcement learning with reward shaping. In Artificial Neural Networks-ICANN 2008, 357\u2013366."},{"key":"S026988891500017X_ref11","doi-asserted-by":"crossref","unstructured":"Marthi B. 2007. Automatic shaping and decomposition of reward functions. In Proceedings of the 24th International Conference on Machine Learning, 608. ACM.","DOI":"10.1145\/1273496.1273572"},{"key":"S026988891500017X_ref13","doi-asserted-by":"publisher","DOI":"10.1002\/9780470316887"},{"key":"S026988891500017X_ref15","volume-title":"Reinforcement Learning: An Introduction","author":"Sutton","year":"1998"},{"key":"S026988891500017X_ref10","doi-asserted-by":"crossref","unstructured":"Grze\u015b M. & Kudenko D. 2008b. Plan-based reward shaping for reinforcement learning. In Proceedings of the 4th IEEE International Conference on Intelligent Systems (IS\u201908), 22\u201329. IEEE.","DOI":"10.1109\/IS.2008.4670492"}],"container-title":["The Knowledge Engineering Review"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.cambridge.org\/core\/services\/aop-cambridge-core\/content\/view\/S026988891500017X","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T14:42:04Z","timestamp":1767624124000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.cambridge.org\/core\/product\/identifier\/S026988891500017X\/type\/journal_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,1]]},"references-count":15,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2016,1]]}},"alternative-id":["S026988891500017X"],"URL":"https:\/\/doi.org\/10.1017\/s026988891500017x","relation":{},"ISSN":["0269-8889","1469-8005"],"issn-type":[{"value":"0269-8889","type":"print"},{"value":"1469-8005","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,1]]}}}