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The optimization of the objective function was achieved by defining the state space, action space, and reward function. The agent\u2019s exploration capability was enhanced through the utilization of a UCB exploration strategy and Boltzmann action exploration. Simulation experiments were conducted using Pycloudsim. The average instruction response time ratio and standard deviation of CPU utilization were compared to measure the advantages and disadvantages of the algorithm. The results indicate that the proposed algorithm surpasses the random, earliest, and RR algorithms in terms of the instruction-to-response time ratio and CPU utilization, demonstrating enhanced efficiency and performance in cloud-task scheduling.<\/jats:p>","DOI":"10.3233\/jcm-247229","type":"journal-article","created":{"date-parts":[[2024,8,16]],"date-time":"2024-08-16T11:51:15Z","timestamp":1723809075000},"page":"2095-2107","source":"Crossref","is-referenced-by-count":1,"title":["Deep Q learning cloud task scheduling algorithm based on improved exploration strategy"],"prefix":"10.66113","volume":"24","author":[{"given":"Chenyu","family":"Cheng","sequence":"first","affiliation":[{"name":"School of Information and Control Engineering, Jilin Institute of Chemical Technology, Jilin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gang","family":"Li","sequence":"additional","affiliation":[{"name":"School of Mechanical and Control Engineering, Baicheng Normal University, Baicheng, Jilin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiaqing","family":"Fan","sequence":"additional","affiliation":[{"name":"School of Information and Control Engineering, Jilin Institute of Chemical Technology, Jilin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"55691","reference":[{"issue":"1","key":"10.3233\/JCM-247229_ref1","doi-asserted-by":"crossref","first-page":"288","DOI":"10.1016\/j.future.2020.02.036","article-title":"Dynamic virtual machine consolidation using a multi-agent system to optimize energy efficiency in cloud computing","volume":"108","author":"Donnell","year":"2020","journal-title":"Future Generation Computer Systems."},{"issue":"124","key":"10.3233\/JCM-247229_ref2","doi-asserted-by":"crossref","first-page":"3507","DOI":"10.1007\/s11277-022-09523-2","article-title":"Load Balancing: DCN Servers based on Regression Analysis During Heavy and Frequent Messages","volume":"4","author":"Begam","year":"2022","journal-title":"Wireless Personal Comminications."},{"key":"10.3233\/JCM-247229_ref3","doi-asserted-by":"crossref","unstructured":"Amini Motlagh, Movaghar, Rahmani. 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