Policy Performance Bounds 论文中给出了三个推论,具体推导过程详见原文或者CPO中的性能差界: 推论1 J(\theta')-J(\theta)\geq \frac{1}{1-\gamma}\underset{\scriptsize{\begin{array}{c}s\sim d_{\theta}(s) \\ a\sim\pi_{\theta'}(a|s)\end{array}}}{E}\left[A^{\pi_\theta}(s,a)...
Constrained Policy Optimization(CPO)[1]是解决CMDP的一个经典算法。通过local policy search + trust region recovery的方法将单步策略更新限定在不违反约束的增长方向上。原理和NPG[2]或TRPO[3]基本相同,区别在于引入了环境约束: 实际操作时候也是进行了一阶和二阶近似: 在只有一个约束时,该问题是有闭式解的(多...
以下是一个简单的 Constrained Policy Optimization (CPO) 算法的 Python 代码示例,它使用 PPO 算法作为基础,并添加了约束条件。 ```python import torch import torch.nn as nn import torch.optim as optim import torch.distributions as D class Actor(nn.Module): def __init__(self, state_dim, action_...
通过阅读2022年发表在ICML上的论文《Constrained Variational Policy Optimization for Safe Reinforcement Learning》,并简要做一下阅读笔记。这篇文章将强化学习问题转换为变分推断的思想进行求解,之前写过类似的博文,如RL——Deep Reinforcement Learning amidst Continual/Lifelong Structured Non-Stationarity,思路都是一样的...
Safe RL——Constrained Policy Optimization (CPO) 作者:凯鲁嘎吉 - 博客园http://www.cnblogs.com/kailugaji/ 这篇文章详细讲解Constrained Policy Optimization (CPO)的公式推导,文献来自于:Joshua Achiam, David Held, Aviv Tamar, Pieter Abbeel. Constrained Policy Optimization. Proceedings of the 34th Internat...
git submodule add -f https://github.com/jachiam/cpo sandbox/cpo Run CPO in the Point-Gather environment with python sandbox/cpo/experiments/CPO_point_gather.py Joshua Achiam, David Held, Aviv Tamar, Pieter Abbeel. "Constrained Policy Optimization".Proceedings of the 34th International Conference...
Recent advances in policy search algorithms (Mnih et al., 2016; Schulman et al., 2015; Lillicrap et al., 2016; Levine et al., 2016) have enabled new capabilities in high-dimensional control, but do not consider the constrained setting. We propose Constrained Policy Optimization (CPO), the...
Recent advances in policy search algorithms (Mnih et al., 2016, Schulman et al., 2015, Lillicrap et al., 2016, Levine et al., 2016) have enabled new capabilities in high-dimensional control, but do not consider the constrained setting. We propose Constrained Policy Optimization (CPO), the...
Constrained Policy Optimization is closely related to safe exploration, which means providing certain degree of safety guarantee during exploration procedure. More about exploration in reinforcement learning can be found inRL-Exploration-Paper-Lists. ...
Env Performance (Dangerous action rate constraint: 10%) FAC CPO TRPO-L PPO-L PB Return 17.08±3.55 25.67±1.96 18.76±1.42 20.48±0.63 PB crate (%) 6.372±1.764 13.19±0.688 10.47±5.357 11.08±0.855 PB Dangerous episodes in 100 tests 3 73 52 66 CG Return 7.51±0.56 18.62±3.25 12.49±...