Guoai Xu, Boya Liu, Guosheng Xu, Peiliang Zuo, Vol. 16, No. 9, September 30, 2022
10.3837/tiis.2022.09.015

• Routing strategy
• Message Forwarding Strategy
• Reinforcement Learning
• VANET
• Black nodes

Yongquan Yang, Cuihua He, Bo Yin, Zhiqiang Wei, Bowei Hong, Vol. 16, No. 6, June 30, 2022
10.3837/tiis.2022.06.006

• Cloud computing
• cloud task scheduling
• Deep Reinforcement Learning
• energy consumption
• proximal policy optimization

Peiqian Liu, Shangchen Xie, Zihao Shen, Hui Wang, Vol. 16, No. 5, May 31, 2022
10.3837/tiis.2022.05.013

• Caching Mechanism
• Deep Reinforcement Learning
• Location Privacy Protection
• Location-based service
• Peer-to-peer network

Huaiwei Si, Guozhen Tan, Yifu Yuan, Yanfei peng, Jianping Li, Vol. 16, No. 3, March 31, 2022
10.3837/tiis.2022.03.003

• Reinforcement Learning
• Multi-agent system
• Explicit Coordination Learning
• Utility Dependence
• Intelligent Vehicle

Chih-Heng Ke, Lia Astuti, Vol. 16, No. 1, January 31, 2022
10.3837/tiis.2022.01.019

• Contention window threshold〖(CW〗_Threshold)
• deep Q-learning network (DQN)
• deep reinforcement learning (DRL)
• smart exponential-threshold-linear backoff algorithm with deep Q-learning network (SETL-DQN)
• wireless networks.

Xiulin Qiu, Yongsheng Xie, Yinyin Wang, Lei Ye, Yuwang Yang, Vol. 15, No. 11, November 30, 2021
10.3837/tiis.2021.11.020

• FANET
• GPSR
• Dynamic Environment
• Multi-Agent Reinforcement Learning
• local information

Yifan Wang, Xin Liu, Mei Wang, Yu Yu, Vol. 15, No. 9, September 30, 2021
10.3837/tiis.2021.09.019

• Environmental Cognition
• Anti-Intelligent Jamming
• Deep Reinforcement Learning
• Hidden Anti-Jamming

Jihun Chae, Namgi Kim, Vol. 15, No. 9, September 30, 2021
10.3837/tiis.2021.09.003

• Multicast tree
• Meta reinforcement learning
• Multimedia routing
• SDN
• Deep Learning

Moonseong Kim, Woochan Lee, Vol. 15, No. 9, September 30, 2021
10.3837/tiis.2021.09.002

• Hopping Sensor
• Mobile IoT
• Reinforcement Learning-based Protocol
• Relocation Protocol
• Sensory Data Networking
• Simulation

Si-yuan Sun, Ying Zheng, Jun-hua Zhou, Jiu-xing Weng, Yi-fei Wei, Xiao-jun Wang, Vol. 15, No. 7, July 31, 2021
10.3837/tiis.2021.07.011

• Deep Reinforcement Learning
• green energy
• heterogeneous service
• Mobile Edge Computing
• power consumption
• Resource Allocation