这时候有个问题就是Value Function也不是从天上掉下来的,因此我们还需要想办法去设计函数拟合这些个Value Function。 当然Advantage Function有很多很多不同的设计,本文目标是介绍应用于PPO的,比较Robust的Generalized Advantage Estimation,GAE。 2Temporal Difference Learning 从Aπ(s,a)=Qπ(s,a)−Vπ(s)式子中...
通过上面的例子可以发现,随着距离终点越来越近,小明的估测值是越来越准的,所以回到前面的公式上,我们写成残差的形式,理论上来说可以使得δt基于当前的局势(at、st、rt),对未来收益的预估更加准确,因为它向最终的结果更近了一步,获得了一个观测值,相当于缩小了估计的范围。 既然如此,为了获得更准的结果,我们可以...
GAE（Generalized Advantage Estimation）是一种改进的策略梯度估计方法，旨在通过考虑不同时间步的观测值，平衡估计的偏差和方差。其核心在于对未来回报的残差估计，通过加权求和k-step的Advantage Estimation，参数[公式]起到了调节这一平衡的关键作用。残差形式的引入，使得价值函数的gradient更准确地逼近真实Re...
We address the first challenge by using value functions to substantially reduce the variance of policy gradient estimates at the cost of some bias, with an exponentially-weighted estimator of the advantage function that is analogous to TD(lambda). We address the second challenge by using trust ...
High- dimensional continuous control using generalized advantage estimation. CoRR, abs/1506.02438, 2015.Schulman, J., Moritz, P., Levine, S., Jordan, M. I., and Abbeel, P. High-dimensional continuous con- trol using generalized advantage estimation. CoRR, abs/1506.02438, 2015b....
Policy gradient methods are an appealing approach in reinforcement learning because they directly optimize the cumulative reward and can straightforwardly be used with nonlinear function approximators such as neural networks. The two main challenges are
The contribution of this method is that it represents a significant step toward a modeling that does not require a cumbersome CFD simulation results for estimation of fragment dynamic and kinematic parameters. Due to this advantage, the model can predict the fragment motion consuming a negligible tim...
It thus enjoys both the advantage of continuous-time modeling and the flexibility of digital implementation. SDGPC is shown to be equivalent to an infinite horizon LQ control law under certain conditions. For well-damped open-loop stable systems, the piecewise constant projected control scenario ...
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Generalized advantage estimation (GAE)是结合了 λ-return方法的优势函数估计,平衡了方差和偏差。尽管这是ICLR2016接收,2015挂arxiv的文章,但至今仍然应用广泛。 论文链接:https://arxiv.org/abs/1506.02438 代码:GitHub - yjhong89/TRPO-GAE: Trust Region Policy Optimization with Generalized Advantage Estimator ...