{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T23:16:06Z","timestamp":1782774966484,"version":"3.54.5"},"reference-count":22,"publisher":"Allerton Press","issue":"2","license":[{"start":{"date-parts":[[2022,4,1]],"date-time":"2022-04-01T00:00:00Z","timestamp":1648771200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,4,1]],"date-time":"2022-04-01T00:00:00Z","timestamp":1648771200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Aut. Control Comp. Sci."],"published-print":{"date-parts":[[2022,4]]},"DOI":"10.3103\/s0146411622020043","type":"journal-article","created":{"date-parts":[[2022,5,18]],"date-time":"2022-05-18T14:03:13Z","timestamp":1652882593000},"page":"130-142","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Hybrid Path Planning Algorithm of the Mobile Agent Based on Q-Learning"],"prefix":"10.3103","volume":"56","author":[{"family":"Tengteng Gao","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Caihong","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guoming","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Na","family":"Guo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Di","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yongdi","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1627","published-online":{"date-parts":[[2022,5,18]]},"reference":[{"key":"7472_CR1","first-page":"296","volume":"34","author":"Q. Wang","year":"2017","unstructured":"Wang, Q., Cheng, J., and Li, X.L., Research on robot path planning method in complex environment, Comput. Simul., 2017, vol. 34, no. 10, pp. 296\u2013300.","journal-title":"Comput. Simul."},{"key":"7472_CR2","unstructured":"Tao, Z., Gao, Y.F., Zheng, T.J., et al., Research on path planning in honeycomb grid map based on A* algorithm, J. North Univ. China (Nat. Sci. Ed.), 2020, vol. 41, no. 4, pp. 310\u2013317."},{"key":"7472_CR3","first-page":"132","volume":"52","author":"D. Wu","year":"2020","unstructured":"Wu, D., Wang, R.F., Fu, X., et al., Research on local path optimization algorithm of mining robot, Coal Eng., 2020, vol. 52, no. 3, pp. 132\u2013136.","journal-title":"Coal Eng."},{"key":"7472_CR4","first-page":"291","volume":"30","author":"J.F. Chen","year":"2020","unstructured":"Chen, J.F., Huang, W.H., Wang, X., et al., Mobile robot path planning based on improved ant colony algorithm, High Technol. Lett., 2020, vol. 30, no. 3, pp. 291\u2013297.","journal-title":"High Technol. Lett."},{"key":"7472_CR5","first-page":"22","volume":"17","author":"H.H. Xiao","year":"2018","unstructured":"Xiao, H.H. and Duan, Y.M., Research on path planning of mobile robot based on improved flower pollination algorithm, Software Guide, 2018, vol. 17, no. 11, pp. 22\u201325.","journal-title":"Software Guide"},{"key":"7472_CR6","first-page":"360","volume":"37","author":"Y. Ren","year":"2020","unstructured":"Ren, Y. and Zhao, H.B., Robot obstacle avoidance and path planning based on improved artificial potential field method, Comput. Simul., 2020, vol. 37, no. 2, pp. 360\u2013364.","journal-title":"Comput. Simul."},{"key":"7472_CR7","first-page":"22","volume":"39","author":"L. Cui","year":"2020","unstructured":"Cui, L. and Zhu, X.J., Research and simulation of service robot intelligent navigation system based on ROS, Sensors Microsyst., 2020, vol. 39, no. 2, pp. 22\u201325.","journal-title":"Sensors Microsyst."},{"key":"7472_CR8","first-page":"3997","volume":"20","author":"K.L. Zheng","year":"2020","unstructured":"Zheng, K.L., Han, B.L., and Wang, X.D., Ackerman robot motion planning system based on improved TEB algorithm, Sci. Technol. Eng., 2020, vol. 20, no. 10, pp. 3997\u20134003.","journal-title":"Sci. Technol. Eng."},{"key":"7472_CR9","first-page":"1504","volume":"41","author":"Y.B. Zheng","year":"2019","unstructured":"Zheng, Y.B., Xi, P.X., Wang, L.L., et al., Multi-agent formation control and obstacle avoidance method based on fuzzy artificial potential field method, Comput. Eng. Sci., 2019, vol. 41, no. 8, pp. 1504\u20131511.","journal-title":"Comput. Eng. Sci."},{"key":"7472_CR10","first-page":"1624","volume":"39","author":"X.L. Ma","year":"2020","unstructured":"Ma, X.L. and Mei, H., Research on mobile robot global path planning based on two-way jump point search algorithm, Mech. Sci. Technol., 2020, vol. 39, no. 10, pp. 1624\u20131631.","journal-title":"Mech. Sci. Technol."},{"key":"7472_CR11","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1007\/s10514-020-09947-4","volume":"45","author":"L. Chang","year":"2021","unstructured":"Chang, L., Shan, L., Jiang, C., and Dai, Y., Reinforcement based mobile robot path planning with improved dynamic window approach in unknown environment, Auton. Robots, 2021, vol.\u00a045, no. 1, pp. 51\u201376. \u00a0https:\/\/doi.org\/10.1007\/s10514-020-09947-4","journal-title":"Auton. Robots"},{"key":"7472_CR12","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-96133-0_20","volume-title":"Reinforcement learning for computer vision and robot navigation, Machine Learning and Data Mining in Pattern Recognition. MLDM 2018","author":"A.V. Bernstein","year":"2018","unstructured":"Bernstein, A.V., Burnaev, E.V., and Kachan, O.N., Reinforcement learning for computer vision and robot navigation, Machine Learning and Data Mining in Pattern Recognition. MLDM 2018, Perner, P., Ed., Lecture Notes in Computer Science, vol. 10935, Cham: Springer, 2018, pp. 258\u2013272. \u00a0https:\/\/doi.org\/10.1007\/978-3-319-96133-0_20"},{"key":"7472_CR13","first-page":"1623","volume":"29","author":"Y. Song","year":"2012","unstructured":"Song, Y., Li, Y.B., and Li, C.H., Mobile robot path planning and reinforcement learning initialization, Control Theory Appl., 2012, vol. 29, no. 12, pp. 1623\u20131628.","journal-title":"Control Theory Appl."},{"key":"7472_CR14","doi-asserted-by":"publisher","first-page":"S177","DOI":"10.1016\/S1672-6529(09)60233-X","volume":"7","author":"L. Lin","year":"2010","unstructured":"Lin, L., Xie, H., Zhang, D., and Shen, L., Supervised neural Q_learning based motion control for bionic underwater robots, J. Bionic Eng., 2010, vol. 7, pp. S177\u2013S184. \u00a0https:\/\/doi.org\/10.1016\/S1672-6529(09)60233-X","journal-title":"J. Bionic Eng."},{"key":"7472_CR15","doi-asserted-by":"publisher","unstructured":"Oh, C.-H., Nakashima, T., and Ishibuchi, H., Initialization of Q-values by fuzzy rules for accelerating Q-learning, IEEE Int. Joint Conf. on Neural Networks Proc. IEEE World Congress on Comput. Intell., Anchorage, Alaska, 1998, IEEE, 1998, vol. 3, pp. 2051\u20132056. \u00a0https:\/\/doi.org\/10.1109\/IJCNN.1998.687175","DOI":"10.1109\/IJCNN.1998.687175"},{"key":"7472_CR16","doi-asserted-by":"publisher","first-page":"657","DOI":"10.4304\/jsw.7.3.657-662","volume":"7","author":"Q. Zhang","year":"2012","unstructured":"Zhang, Q., Li, M., Wang, X., and Zhang, Y., Reinforcement learning in robot path optimization, J. Software, 2012, vol. 7, no. 3, pp. 657\u2013662. \u00a0https:\/\/doi.org\/10.4304\/jsw.7.3.657-662","journal-title":"J. Software"},{"key":"7472_CR17","doi-asserted-by":"publisher","first-page":"205","DOI":"10.1613\/jair.1190","volume":"19","author":"E. Wiewiora","year":"2003","unstructured":"Wiewiora, E., Potential-based shaping and Q-value initialization are equivalent, J. Artif. Intell. Res., 2003, vol.\u00a019, no. 1, pp. 205\u2013208. \u00a0https:\/\/doi.org\/10.1613\/jair.1190","journal-title":"J. Artif. Intell. Res."},{"key":"7472_CR18","first-page":"314","volume":"27","author":"X.S. Xu","year":"2019","unstructured":"Xu, X.S. and Yuan, J., Path planning method for mobile robot based on improved reinforcement learning, J.\u00a0Chin. Inertial Technol., 2019, vol. 27, no. 3, pp. 314\u2013320.","journal-title":"J.\u00a0Chin. Inertial Technol."},{"key":"7472_CR19","first-page":"129","volume":"54","author":"P.F. Dong","year":"2018","unstructured":"Dong, P.F., Zhang, Z.A., Mei, X.H., et al., Reinforcement learning path planning algorithm introducing potential field and trap search, Comput. Eng. Appl., 2018, vol. 54, no. 16, pp. 129\u2013134.","journal-title":"Comput. Eng. Appl."},{"key":"7472_CR20","first-page":"141","volume":"38","author":"C. Li","year":"2019","unstructured":"Li, C., Li, M.J., and Du, J.J., An improved method of reinforcement learning action strategy \u03b5-greedy, Comput. Technol. Autom., 2019, vol. 38, no. 2, pp. 141\u2013145.","journal-title":"Comput. Technol. Autom."},{"key":"7472_CR21","unstructured":"Zhang, H., Research and implementation of unmanned vehicle path planning based on reinforcement learning, PhD Dissertation, Jining, China: Qufu Normal Univ., 2019."},{"key":"7472_CR22","doi-asserted-by":"publisher","unstructured":"Yang, X.S., Flower pollination algorithm for global optimization, Unconventional Computation and Natural Computation. UCNC 2012, Durand-Lose, J. and Jonoska, N., Eds., Lecture Notes in Computer Science, vol.\u00a07445, Berlin: Springer, 2012, pp. 240\u2013249. \u00a0https:\/\/doi.org\/10.1007\/978-3-642-32894-7_27","DOI":"10.1007\/978-3-642-32894-7_27"}],"container-title":["Automatic Control and Computer Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.3103\/S0146411622020043.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.3103\/S0146411622020043","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.3103\/S0146411622020043.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,15]],"date-time":"2026-03-15T22:03:21Z","timestamp":1773612201000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.3103\/S0146411622020043"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,4]]},"references-count":22,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2022,4]]}},"alternative-id":["7472"],"URL":"https:\/\/doi.org\/10.3103\/s0146411622020043","relation":{},"ISSN":["0146-4116","1558-108X"],"issn-type":[{"value":"0146-4116","type":"print"},{"value":"1558-108X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,4]]},"assertion":[{"value":"18 January 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 July 2021","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 July 2021","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 May 2022","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}