{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,26]],"date-time":"2025-11-26T15:55:12Z","timestamp":1764172512073,"version":"build-2065373602"},"reference-count":31,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2022,3,19]],"date-time":"2022-03-19T00:00:00Z","timestamp":1647648000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Shanghai Action Plan of Technological Innovation","award":["20DZ1201400","22ZR1416500"],"award-info":[{"award-number":["20DZ1201400","22ZR1416500"]}]},{"name":"Shanghai Sailing Program","award":["20YF1410900"],"award-info":[{"award-number":["20YF1410900"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Space exploration is a hot topic in the application field of mobile robots. Proposed solutions have included the frontier exploration algorithm, heuristic algorithms, and deep reinforcement learning. However, these methods cannot solve space exploration in time in a dynamic environment. This paper models the space exploration problem of mobile robots based on the decision-making process of the cognitive architecture of Soar, and three space exploration heuristic algorithms (HAs) are further proposed based on the model to improve the exploration speed of the robot. Experiments are carried out based on the Easter environment, and the results show that HAs have improved the exploration speed of the Easter robot at least 2.04 times of the original algorithm in Easter, verifying the effectiveness of the proposed robot space exploration strategy and the corresponding HAs.<\/jats:p>","DOI":"10.3390\/e24030426","type":"journal-article","created":{"date-parts":[[2022,3,20]],"date-time":"2022-03-20T21:26:22Z","timestamp":1647811582000},"page":"426","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["A Soar-Based Space Exploration Algorithm for Mobile Robots"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7062-4404","authenticated-orcid":false,"given":"Fei","family":"Luo","sequence":"first","affiliation":[{"name":"School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6857-6362","authenticated-orcid":false,"given":"Qin","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0517-1231","authenticated-orcid":false,"given":"Joel","family":"Fuentes","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Information Technologies, Universidad del B\u00edo-B\u00edo, Chill\u00e1n 3780000, Chile"}]},{"given":"Weichao","family":"Ding","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China"}]},{"given":"Chunhua","family":"Gu","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,3,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1186\/s40638-016-0055-x","article-title":"Mobile robots exploration through cnn-based reinforcement learning","volume":"3","author":"Tai","year":"2016","journal-title":"Robot. 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