{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T20:38:36Z","timestamp":1762547916521,"version":"build-2065373602"},"reference-count":0,"publisher":"Association for the Advancement of Artificial Intelligence (AAAI)","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["AIIDE"],"abstract":"<jats:p>Narrative planning can be used to create structured interactive experiences that dynamically respond to user input. Narrative planning works by generating a sequence of actions that achieves an author's desired goal while ensuring that there is an explanation for why each character takes each action in the sequence. An action in a sequence is considered necessary to that sequence if leaving the action out would prevent a later action in the sequence from being taken or prevent an author or character goal from being achieved. Using this definition, we define the causal width of a sequence to be the number of causally unnecessary actions, and we hypothesize sequences with a lower causal width are more likely to lead to a solution. We show that using causal width as a ranking mechanism can sometimes improve blind search, and ignoring stories with a high causal width can always improve the performance of heuristic search on a set of story benchmark problems.<\/jats:p>","DOI":"10.1609\/aiide.v21i1.36823","type":"journal-article","created":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T20:34:20Z","timestamp":1762547660000},"page":"196-205","source":"Crossref","is-referenced-by-count":0,"title":["Speeding Up Narrative Planning with Causal Width Search and Pruning"],"prefix":"10.1609","volume":"21","author":[{"given":"Gage","family":"Birchmeier","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stephen G.","family":"Ware","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"9382","published-online":{"date-parts":[[2025,11,7]]},"container-title":["Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment"],"original-title":[],"link":[{"URL":"https:\/\/ojs.aaai.org\/index.php\/AIIDE\/article\/download\/36823\/38961","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/ojs.aaai.org\/index.php\/AIIDE\/article\/download\/36823\/38961","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T20:34:20Z","timestamp":1762547660000},"score":1,"resource":{"primary":{"URL":"https:\/\/ojs.aaai.org\/index.php\/AIIDE\/article\/view\/36823"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,7]]},"references-count":0,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,11,7]]}},"URL":"https:\/\/doi.org\/10.1609\/aiide.v21i1.36823","relation":{},"ISSN":["2334-0924","2326-909X"],"issn-type":[{"value":"2334-0924","type":"electronic"},{"value":"2326-909X","type":"print"}],"subject":[],"published":{"date-parts":[[2025,11,7]]}}}