{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,12]],"date-time":"2024-08-12T17:52:26Z","timestamp":1723485146439},"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":[[2018,7]]},"abstract":"<jats:p>Interactive narrative planning offers significant potential for creating adaptive gameplay experiences. While data-driven techniques have been devised that utilize player interaction data to induce policies for interactive narrative planners, they require enormously large gameplay datasets. A promising approach to addressing this challenge is creating simulated players whose behaviors closely approximate those of human players. In this paper, we propose a novel approach to generating high-fidelity simulated players based on deep recurrent highway networks and deep convolutional networks. Empirical results demonstrate that the proposed models significantly outperform the prior state-of-the-art in generating high-fidelity simulated player models that accurately imitate human players\u2019 narrative interactions. Using the high-fidelity simulated player models, we show the advantage of more exploratory reinforcement learning methods for deriving generalizable narrative adaptation policies.<\/jats:p>","DOI":"10.24963\/ijcai.2018\/540","type":"proceedings-article","created":{"date-parts":[[2018,7,5]],"date-time":"2018-07-05T05:49:10Z","timestamp":1530769750000},"page":"3884-3890","source":"Crossref","is-referenced-by-count":6,"title":["High-Fidelity Simulated Players for Interactive Narrative Planning"],"prefix":"10.24963","author":[{"given":"Pengcheng","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Computer Science, North Carolina State University, Raleigh, NC 27695, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jonathan","family":"Rowe","sequence":"additional","affiliation":[{"name":"Department of Computer Science, North Carolina State University, Raleigh, NC 27695, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wookhee","family":"Min","sequence":"additional","affiliation":[{"name":"Department of Computer Science, North Carolina State University, Raleigh, NC 27695, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bradford","family":"Mott","sequence":"additional","affiliation":[{"name":"Department of Computer Science, North Carolina State University, Raleigh, NC 27695, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"James","family":"Lester","sequence":"additional","affiliation":[{"name":"Department of Computer Science, North Carolina State University, Raleigh, NC 27695, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"10584","event":{"number":"27","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"acronym":"IJCAI-2018","name":"Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}","start":{"date-parts":[[2018,7,13]]},"theme":"Artificial Intelligence","location":"Stockholm, Sweden","end":{"date-parts":[[2018,7,19]]}},"container-title":["Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2018,7,5]],"date-time":"2018-07-05T05:53:46Z","timestamp":1530770026000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2018\/540"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2018,7]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2018\/540","relation":{},"subject":[],"published":{"date-parts":[[2018,7]]}}}