简介:【5分钟 Paper】(TD3) Addressing Function Approximation Error in Actor-Critic Methods 论文题目:Addressing Function Approximation Error in Actor-Critic Methods 所解决的问题? value-base的强化学习值函数的近似估计会过估计值函数(DQN),作者将Double Q-Learning处理过拟合的思想引入actor critic算法中...
Addressing Function Approximation Error in Actor-Critic Methods 1.研究内容 Double Q-learning是value-based类算法里面用来消除overestimation bias的方法,这篇文章研究了actor-critic类算法里面消除overestimation bias的方法。同时,还研究了target network在TD update中消除累积误差的作用。 2.研究方法(公式理论推导) 这个...
在本节中,我们强调最小化每次更新时的误差,建立目标网络与估计误差之间的联系以及对actor-critic的学习过程进行修改以减少方差的重要性。 5.1. Accumulating Error 由于时序差分更新,其中根据后续状态的估计来构建价值函数的估计,因此会产生误差。尽管可以合理地期望单个更新的误差很小,但是这些估计误差可能会累积,从而可能...
Round-off errorUnbounded likelihoodThe joint probability density function, evaluated at the observed data, is commonly used as the likelihood function to compute maximum likelihood estimates. For some models, however, there exist paths in the parameter space along which this density-approximation ...
This is achieved via developing a bound on eigenvalues as a function of the domain size. Then we prove that for a chosen number of terms in the KL expansion with any kernel for a one-dimensional process, the approximation error in the trace norm reduces with the domain size. Based on ...
However, this error does not necessarily guarantee specificity of addressing, where a given ligand combination should activate only a single cell type and not the others. To quantify the performance of each system, we analyzed the distributions of on-target and off-target activation levels. We ...
Raab M, Steger A (1998) “balls into bins’’—a simple and tight analysis. In: Luby M, Rolim JDP, Serna M (eds) Randomization and approximation techniques in computer science. Springer, Berlin, Heidelberg, pp 159–170 Rajwar K, Deep K, Das S (2023) An exhaustive review of the metah...
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Error bounds derivation In this section, we derive a numerical bound RB on the rotation error and an analytical bound TB on the translation error. To create the numerical bound RB for the rotation error, we generate a set of \(K=1,000,000\) random rotation matrices \(R^\text {rand} ...
Thus the approximation for the sum of the two metric is: log(ex1+ex2)≈max(x1,x2)+logtable(|x1−x2|), (ii) [0010] where logtable(|x1−x2|) is an N-entry look up table. It has been shown that as few as 8 entries is sufficient to achieve negligible bit error or frame ...