{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,6]],"date-time":"2024-09-06T14:36:52Z","timestamp":1725633412733},"reference-count":20,"publisher":"IEEE","license":[{"start":{"date-parts":[[2020,8,1]],"date-time":"2020-08-01T00:00:00Z","timestamp":1596240000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,8,1]],"date-time":"2020-08-01T00:00:00Z","timestamp":1596240000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,8,1]],"date-time":"2020-08-01T00:00:00Z","timestamp":1596240000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,8]]},"DOI":"10.1109\/cog47356.2020.9231691","type":"proceedings-article","created":{"date-parts":[[2020,10,21]],"date-time":"2020-10-21T18:05:50Z","timestamp":1603303550000},"page":"283-290","source":"Crossref","is-referenced-by-count":1,"title":["Rinascimento: using event-value functions for playing Splendor"],"prefix":"10.1109","author":[{"given":"Ivan","family":"Bravi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Simon M.","family":"Lucas","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref10","article-title":"Automated playtesting with procedural personas with evolved heuristics","author":"holmgard","year":"2018","journal-title":"IEEE Transactions on Games"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CIG.2014.6932868"},{"key":"ref12","first-page":"4055","article-title":"Successor features for transfer in reinforcement learning","author":"barreto","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1993.5.4.613"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CIG.2019.8848028"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/NICOInt.2019.00032"},{"article-title":"Efficient evolutionary methods for game agent optimisation: Model-based is best","year":"2019","author":"lucas","key":"ref16"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CEC.2018.8477869"},{"key":"ref18","first-page":"2","article-title":"Alphastar: Mastering the real-time strategy game starcraft ii","author":"vinyals","year":"2019","journal-title":"DeepMind blog"},{"article-title":"Illuminating search spaces by mapping elites","year":"2015","author":"mouret","key":"ref19"},{"article-title":"Mastering chess and shogi by self-play with a general reinforcement learning algorithm","year":"2017","author":"silver","key":"ref4"},{"article-title":"Playing atari with deep reinforcement learning","year":"2013","author":"mnih","key":"ref3"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TG.2019.2901021"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1613\/jair.3912"},{"key":"ref8","first-page":"2930","article-title":"Playing hard exploration games by watching youtube","author":"aytar","year":"2018","journal-title":"Advances in neural information processing systems"},{"article-title":"Observe and look further: Achieving consistent performance on atari","year":"2018","author":"pohlen","key":"ref7"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/2463372.2463413"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TCIAIG.2012.2186810"},{"article-title":"Learning montezuma&#x2019;s revenge from a single demonstration","year":"2018","author":"salimans","key":"ref9"},{"article-title":"Apocrita - High Performance Computing Cluster for Queen Mary University of London","year":"2017","author":"king","key":"ref20"}],"event":{"name":"2020 IEEE Conference on Games (CoG)","start":{"date-parts":[[2020,8,24]]},"location":"Osaka, Japan","end":{"date-parts":[[2020,8,27]]}},"container-title":["2020 IEEE Conference on Games (CoG)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9222389\/9231525\/09231691.pdf?arnumber=9231691","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,27]],"date-time":"2022-06-27T15:45:26Z","timestamp":1656344726000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9231691\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,8]]},"references-count":20,"URL":"https:\/\/doi.org\/10.1109\/cog47356.2020.9231691","relation":{},"subject":[],"published":{"date-parts":[[2020,8]]}}}