In the originalDPG paper, under section 4.2. you could see that DDPG is a type of "Off-Policy Deterministic Actor-Critic" algorithm. Section 4.2 of the DPG paper explains why the DPG can work for off-policy cases. For further understanding, you can contrast this with section 2.4 of the ...
DPG(Deterministic Policy Gradient)[2]: 即同轨确定策略梯度 将SPG中的随机性策略 \pi_\theta(\cdot \mid s) 变成成确定性策略 \mu_\theta(s) 以处理连续动作空间,如此策略将输出某个具体的动作值,而不再是若干个动作的概率。 此时目标函数为 J(\mu_\theta)=\int_{s \in \mathcal{S}} \rho_0(...
在这种情况下,将策略称为actor,将价值函数称为critic。许多actor-critic算法都建立在标准同策策略梯度公式基础上,以更新actor(Peters&Schaal, 2008),其中许多工作还考虑了策略的熵,但是他们没有使用它来最大化熵,而是使用它作为正则化器(Schulman et al., 2017b; 2015; Mnih et al., 2016; Gruslys et al., ...
使用与上下文相同的异策RL批次("off-policy RL-batch") 结果如图6所示。采样上下文异策会严重影响性能。在这种情况下,对RL和上下文使用相同的批次会有所帮助,也许是因为相关性使学习变得更容易。总体而言,这些结果证明了异策元RL中谨慎进行数据采样的重要性。 Deterministic context.最后,我们研究了将隐上下文建模为概...
We show that conservative Q-Prop provides substantial gains in sample efficiency over trust region policy optimization (TRPO) with generalized advantage estimation (GAE), and improves stability over deep deterministic policy gradient (DDPG), the state-of-the-art on-policy and off-policy methods, on...
The control problem most commonly addressed in the contemporary literature is to find an optimal policy which maximizes the value function, i.e., the long run discounted reward of the MDP. The current settings also assume access to a generative model of the MDP with the hidden premise that ...
Optimization (PPO) performs better than off-policy learning with Deep Deterministic Policy Gradient (DDPG) when both are combined with a CBF for safe load... L Dinh,PTA Quang,J Leguay - IEEE 被引量: 0发表: 2024年 Reinforcement learning for intensive care medicine: actionable clinical insights...
[15] present a actor-critic-identifier structure based on neural network (NN), and obtain the approximate Nash equilibrium of multi-player NZS differential games for nonlinear deterministic system. Ren et al. [16] use off-policy learning mechanism based on IRL technique to solve multi-player ...
并不包含其他的限定,例如是否为 On-Policy 或者 Off-Policy。对于 On-Policy 的 Deterministic Actor-Critc算法,值函数为 Q^{w}(s, a), 确定策略为 \mu_{\theta}(s) , 我们可以建立如下目标函数: \begin{aligned} J(w) &=\operatorname{minimize}_{w} E_{\pi}\left[\frac{1}{2}\left(r_{t...
^Silver D, Lever G, Heess N, et al. Deterministic policy gradient algorithms[C]//International ...