We used the Deep Deterministic Policy Gradient (DDPG) variant, which adapts to continuous data and improves the secrecy rate by considering, in the algorithm, the best sample obtained via a Prioritized Experiment Replay (PER).Lammari, Amina...
切换阈值等动态信息构建越区切换模型.同时针对算法时间成本复杂度及稳定性,采用优先经验回放深度确定性策略梯度(Prioritized Experience Replay-Deep Deterministic Policy Gradient,PER-DDPG)算法,将列车状态空间信息传输至PER-DDPG网络中进行优化分析.结果表明基于PER-DDPG算法优化后的列车越区切换模型使用该算法时间计算成本...
基于PERDDPG的移动边缘计算任务卸载仿真平台是由广西大学著作的软件著作,该软件著作登记号为:2022SR0352494,属于分类,想要查询更多关于基于PERDDPG的移动边缘计算任务卸载仿真平台著作的著作权信息就到天眼查官网!
Clean, Robust, and Unified PyTorch implementation of popular Deep Reinforcement Learning (DRL) algorithms (Q-learning, Duel DDQN, PER, C51, Noisy DQN, PPO, DDPG, TD3, SAC, ASL) - collapse-del/DRL-Pytorch
切换阈值等动态信息构建越区切换模型.同时针对算法时间成本复杂度及稳定性,采用优先经验回放深度确定性策略梯度(Prioritized Experience Replay-Deep Deterministic Policy Gradient,PER-DDPG)算法,将列车状态空间信息传输至PER-DDPG网络中进行优化分析.结果表明基于PER-DDPG算法优化后的列车越区切换模型使用该算法时间计算成本...
Clean, Robust, and Unified PyTorch implementation of popular Deep Reinforcement Learning (DRL) algorithms (Q-learning, Duel DDQN, PER, C51, Noisy DQN, PPO, DDPG, TD3, SAC, ASL) Topics machine-learning reinforcement-learning asl deep-reinforcement-learning q-learning pytorch ddpg sac double-dqn...
Clean, Robust, and Unified PyTorch implementation of popular Deep Reinforcement Learning (DRL) algorithms (Q-learning, Duel DDQN, PER, C51, Noisy DQN, PPO, DDPG, TD3, SAC, ASL) - XinJingHao/DRL-Pytorch