{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,15]],"date-time":"2025-10-15T00:37:12Z","timestamp":1760488632247,"version":"build-2065373602"},"reference-count":14,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2015,7,30]],"date-time":"2015-07-30T00:00:00Z","timestamp":1438214400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Polish National Science Centre","award":["2011\/01\/D\/ST6\/06146"],"award-info":[{"award-number":["2011\/01\/D\/ST6\/06146"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Automated planning is a well-established field of artificial intelligence (AI), with applications in route finding, robotics and operational research, among others. The task of developing a plan is often solved by finding a path in a graph representing the search domain; a robust plan consists of numerous paths that can be chosen if the execution of the best (optimal) one fails. While robust planning for a single entity is rather simple, development of a robust plan for multiple entities in a common environment can lead to combinatorial explosion. This paper proposes a novel hybrid approach, joining heuristic search and the wavefront algorithm to provide a plan featuring robustness in areas where it is needed, while maintaining a low level of computational complexity.<\/jats:p>","DOI":"10.3390\/e17085422","type":"journal-article","created":{"date-parts":[[2015,7,30]],"date-time":"2015-07-30T11:21:59Z","timestamp":1438255319000},"page":"5422-5436","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["A Robust Planning Algorithm for Groups of Entities in Discrete Spaces"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4406-4992","authenticated-orcid":false,"given":"Igor","family":"Wojnicki","sequence":"first","affiliation":[{"name":"AGH University of Science and Technology, Al. Mickiewicza 30, Krak\u00f3w, 30-059, Poland"}]},{"given":"Sebastian","family":"Ernst","sequence":"additional","affiliation":[{"name":"AGH University of Science and Technology, Al. Mickiewicza 30, Krak\u00f3w, 30-059, Poland"}]},{"given":"Wojciech","family":"Turek","sequence":"additional","affiliation":[{"name":"AGH University of Science and Technology, Al. Mickiewicza 30, Krak\u00f3w, 30-059, Poland"}]}],"member":"1968","published-online":{"date-parts":[[2015,7,30]]},"reference":[{"key":"ref_1","unstructured":"Russell, S.J., and Norvig, P. (2002). Artificial Intelligence: A Modern Approach, Prentice Hall. [2nd ed.]."},{"key":"ref_2","first-page":"103","article-title":"Software Agent Systems for Improving Performance of Multi-Robot Groups","volume":"112","author":"Turek","year":"2011","journal-title":"Fundam. Inf."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Blaszczyk, P., Turek, W., and Cetnarowicz, K. (2013, January 26\u201329). 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