TD3(参考了double Q-learning的思想来优化critic,延缓actor的更新,计算critic的优化目标时在action上加一个小扰动) 1.2. PPO(Proximal Policy Optimization Algorithms) PPO是TRPO(Trust Region Policy Optimization)的简化版,二者的目标都是:在PG算法的优化过程中,使性能单调上升,并且使上升的幅度尽量大。 PPO同样使用...
[Python] Soft Actor-Critic算法实现 以下是PyTorch中Soft Actor-Critic (SAC)算法的完整实现: 1.参数设置 代码语言:javascript 代码运行次数:0 运行 AI代码解释 """《SAC,Soft Actor-Critic算法》 时间:2024.12作者:不去幼儿园"""importtorch # 引入 PyTorch 库,用于构建和训练深度学习模型importtorch.nnasnn #...
Application of Soft Actor-Critic Algorithms in Optimizing Wastewater Treatment with Time Delays IntegrationWastewater treatment plants face unique challenges for process control due to their complex dynamics, slow time constants, and stochastic delays in observations and actions. These characteristics make ...
Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor, Haarnoja et al, 2018. 将Soft Q learning与Actor-Critic框架结合,提出了SAC-v1。该算法中,学习Q网络,V网络以及Actor网络,熵系数恒定。 Soft actor-critic algorithms and applications, Haarnoja et al, 2018...
Soft Actor-Critic Algorithms and Applications. arXiv preprint arXiv:1812.05905. 2018. """ def __init__( self, training_environment, evaluation_environment, policy, Qs, plotter=None, policy_lr=3e-4, Q_lr=3e-4, alpha_lr=3e-4, reward_scale=1.0, target_entropy='auto', discount=0.99, ...
第三篇:《Soft Actor-Critic Algorithms and Applications》 这篇论文在第二篇的基础上彻底吸收了DDPG和TD3的优势,简化了网络结构,提出了动态修改超参数 αα 的方法,是最终版本的SAC。一、基本问题强化学习可以用来优化确定性策略和随机策略。但是目前大多数主流算法(DDPG、TD3、PPO等等)最终都是优化了一个确定性...
"Soft Actor-Critic Algorithms and Application." Preprint, submitted January 29, 2019. https://arxiv.org/abs/1812.05905. [2] Christodoulou, Petros. "Soft Actor-Critic for Discrete Action Settings." arXiv preprint arXiv:1910.07207 (2019). https://arxiv.org/abs/1910.07207. [3] Delalleau, ...
"""Soft Actor-Critic (SAC) References --- [1] Tuomas Haarnoja*, Aurick Zhou*, Kristian Hartikainen*, George Tucker, Sehoon Ha, Jie Tan, Vikash Kumar, Henry Zhu, Abhishek Gupta, Pieter Abbeel, and Sergey Levine. Soft Actor-Critic Algorithms and Applications....
Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor, Haarnoja et al, 2018 Soft Actor-Critic Algorithms and Applications, Haarnoja et al, 2018 Learning to Walk via Deep Reinforcement Learning, Haarnoja et al, 2018 Other Public Implementations SAC release...
p2.Soft Actor-Critic Algorithms and Applications 文章对SAC的方法总结了有三个要点: Actor-critic框架(由两个网络分别近似policy和value function/ q-function) Off-policy(提高样本使用效率) Entropy来保证stable和exploration 注:要理解SAC算法关键是要理解其中的soft和entropy。 2.基础说明 2.1 Actor-critic框架 ...