{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T12:04:45Z","timestamp":1784203485369,"version":"3.55.0"},"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":[[2026,7]]},"abstract":"<jats:p>We develop an Answer Set Programming (ASP)-based approach for\ncomputing the smallest bidirectional macro schemes (BMSs),\na fundamental NP-hard optimization problem in dictionary-based compression.\nOur approach relies on high-level ASP encodings and delegates both the\ngrounding and solving tasks to an off-the-shelf ASP solver.\nThe proposed encoding is compact and extensible, and\nleverages advanced ASP techniques to improve scalability,\nincluding ASP modulo acyclicity and refined declarative encodings of acyclicity constraints.\nWe further show that our ASP encoding can be naturally extended to compute\nthe smallest straight-line programs (SLPs),\nanother important NP-hard measure of repetitiveness.\nFurthermore, we establish the competitiveness of our approach by\nempirically contrasting it with a more dedicated MaxSAT-based approach.<\/jats:p>","DOI":"10.24963\/kr.2026\/66","type":"proceedings-article","created":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T11:15:53Z","timestamp":1784200553000},"page":"700-710","source":"Crossref","is-referenced-by-count":0,"title":["Optimal Dictionary-Based Compression with Answer Set Programming: Encodings and Empirical Analysis"],"prefix":"10.24963","author":[{"given":"Mutsunori","family":"Banbara","sequence":"first","affiliation":[{"name":"Nagoya University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hideo","family":"Bannai","sequence":"additional","affiliation":[{"name":"Institute of Science Tokyo"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Takashi","family":"Horiyama","sequence":"additional","affiliation":[{"name":"Hokkaido University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dominik","family":"K\u00f6ppl","sequence":"additional","affiliation":[{"name":"University of Yamanashi"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Takuya","family":"Mieno","sequence":"additional","affiliation":[{"name":"The University of Electro-Communications"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hidetomo","family":"Nabeshima","sequence":"additional","affiliation":[{"name":"University of Yamanashi"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"10584","event":{"name":"23nd International Conference on Principles of Knowledge Representation and Reasoning {KR-2026}","theme":"Artificial Intelligence","location":"Lisbon, Portuagal","acronym":"KR-2026","number":"23","sponsor":["Artificial Intelligence Journal","Principles of Knowledge Representation and Reasoning Inc.","European Association for Artificial Intelligence"],"start":{"date-parts":[[2026,7,20]]},"end":{"date-parts":[[2026,7,18]]}},"container-title":["Proceedings of the TwentyThird International Conference on Principles of Knowledge Representation and Reasoning"],"original-title":[],"deposited":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T11:16:11Z","timestamp":1784200571000},"score":1,"resource":{"primary":{"URL":"https:\/\/proceedings.kr.org\/2026\/66"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2026,7]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/kr.2026\/66","relation":{},"subject":[],"published":{"date-parts":[[2026,7]]}}}