Routing Optimization Algorithm Based on Twin Delayed Deep Deterministic Policy Gradient
ZHENG Yi
HAN Yongguo
Abstract：With the rapid development of artificial intelligence,network communication,network application,traditional rout-ing algorithms such as RIP and OSPF have a series of problems such as slow convergence and high average delay in the face of expo-nential growth of network traffic and different service requirements.In recent years,deep reinforcement learning has made great progress in the field of complex control.Routing optimization algorithm is essentially a control optimization problem.In order to over-come the drawbacks of existing routing algorithms in some situations,and combine deep reinforcement learning with computer rout-ing optimization,this paper proposes an improved DDPG algorithm named TD3OR algorithm to solve the drawbacks of traditional routing in some situations.The experiment shows that the route using TD3OR algorithm has lower delay than that using DDPG algo-rithm and traditional OSPF algorithm,which proves that TD3OR algorithm is effective.
Keywords：deep reinforcement learningDDPGTD3ORrouting optimization
Publication Date：2025-08-20
Online Publishing Date：2025-12-12(First online date of this platform, not the publication date of the document)
Pages：5( 2117-2121 )