Results 161 to 170 of about 6,304,901 (198)

Joint Task Offloading and Resource Allocation with Data Caching in UAV-Aided Mobile Edge Computing Networks for Latency-Sensitive Applications. [PDF]

Sensors (Basel)
Baidya T, Moh S.
europepmc   +1 more source

Expert-guided optimization for load transfer in distribution networks assisted by virtual power plants. [PDF]

PLoS One
Chen L, Fang J, Lv X, Zhang L, Zhou Y, Zhou M.   +5 more
europepmc   +1 more source

Energy collaborative optimization of power routing based on PPO and generative adversarial imitation learning. [PDF]

PLoS One
Lyu J, Huang J.
europepmc   +1 more source

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PPO-TA: Adaptive task allocation via Proximal Policy Optimization for spatio-temporal crowdsourcing

Knowledge-Based Systems, 2023
Hongbin Dong, Tingwei Pan
exaly   +2 more sources

Improving proximal policy optimization with alpha divergence

Neurocomputing, 2023
Proximal policy optimization (PPO) is a recent advancement in reinforcement learning, which is formulated as an unconstrained optimization problem including two terms: accumulative discount return and Kullback–Leibler (KL) divergence.
Junyu Xuan, Guangquan Zhang, Haotian Xu
exaly   +2 more sources

Entropy adjustment by interpolation for exploration in Proximal Policy Optimization (PPO)

Engineering Applications of Artificial Intelligence
Ayoub Boudlal, Abderahim Khafaji, Jamal Elabbadi   +2 more
exaly   +3 more sources

PPO-RM: Proximal Policy Optimization Based Route Mutation for Multimedia Services

2021 International Wireless Communications and Mobile Computing (IWCMC), 2021
The growing multimedia services have brought unprecedented challenges to the traditional static network architecture. Moving Target Defense (MTD) has been proposed to solve the inherent disadvantages of existing defense techniques. As an important area of MTD research, Route Mutation (RM) can dynamically change the forwarding routes in the network.
Jiahao Shen, Tao Zhang 0063, Bingchi Zhang, Weixiao Ji, Xiaohui Kuang, Changqiao Xu   +5 more
openaire   +2 more sources

Fast-PPO: Proximal Policy Optimization with Optimal Baseline Method

2020 IEEE International Conference on Progress in Informatics and Computing (PIC), 2020
Deep deterministic policy gradient (DDPG) is a useful deep reinforcement learning approach, but it tends to suffer from instability of gradient estimates. Recent methods such as PPO just limit the policy update under lower speed to keep stability by chance. In this paper, we model the problem under an advantage actor-critic(A2C) architecture.
Zhu Xiao, Ning Xie, Guobiao Yang, Zhenjiang Du   +3 more
openaire   +1 more source

Traffic scheduling algorithm with time constraint based on proximal policy optimization (PPO) algorithm

Eighth International Conference on Traffic Engineering and Transportation System (ICTETS 2024)
XiRong Wang, ChangXu Wang, ZhengShi Zhang, Dong Si   +3 more
exaly   +2 more sources

KAN-PPO: A Fast Convergence and Stable Proximal Policy Optimization Powered by Kolmogorov–Arnold Network

Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering
Honghao Gao, Xinheng Wang, Muddesar Iqbal   +2 more
exaly   +2 more sources