Research on Resource Scheduling of Cloud Call Center Based on Deep Reinforcement Learning
ZHANG Rongxun
FU Xiong
WANG Junchang
Abstract：Aiming at the problems of limited time-frequency resource constraints and high-concurrency in the cloud call cen-ter,an automatic scheduling algorithm for communication lines based on deep reinforcement learning is proposed.Firstly,a homoge-neous multi-agent system is modeled by using a Markov decision process,and a composite reward function is designed.Subsequent-ly,from the perspective of sequential decision-making,a multiple self-attention mechanism is designed,and three algorithms based on the Actor-Critic architecture are used to train the model.The experimental results show that,the model can automatically output the joint scheduling strategy,which has excellent stability and effectiveness.
Keywords：cloud call centermulti-agent systemdeep reinforcement learningattention mechanism
Publication Date：2025-11-20
Online Publishing Date：2026-01-28(First online date of this platform, not the publication date of the document)
Pages：7( 3006-3012 )