Deisenroth, Probabilistic inference for fast learning in control, in: S. Girgin, M. Loth, R. Munos, P. Preux, D. Ryabko (Eds.), Recent Advances in Reinforcement Learning, Lecture Notes on Computer Science, vol. 5323, Springer, Berlin, November 2008, pp. 229-242....
RL与概率推断模型(probabilistic inference)之间的关联并不明显. 但这项研究在算法方面的好处显而易见: 将RL问题转换为概率推断模型,可以引入很多approximate inference tools. RL和最优化问题(Optimal Control problem)通常可以用最大熵(Maximum Entropy RL)方法分析. 我们认为: Deterministic Dynamics 问题等价于 Probabi...
推荐大神 Sergey Levine 的一篇文章: Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Review 链接: https://arxiv.org/abs/1805.00909
Reinforcement learning for closed-loop regulation of cardiovascular system with vagus nerve stimulation: a computational study two approaches; a general policy using deep RL algorithms and a sample-efficient adaptive policy using probabilistic inference for learning and control. Main... P Sarikhani,HL ...
A new class of fuzzy inference system is introduced, a probabilistic fuzzy inference system, for the modeling and control problems, one that model and mini... N Sozhamadevi,S Sathiyamoorthy - 《Arabian Journal for Science & Engineering》 被引量: 6发表: 2015年 Significance measures for rules...
derive inference methods for models. Since deriving and implementing inference methods is generally the most rate-limiting and bug-prone step in modelling, often taking months, automating this step so that it takes minutes or seconds will greatly accelerate the deployment of machine learning systems....
内容提示: Probabilistic Inference in Reinforcement LearningDone RightJean TarbouriechGoogle DeepMindjtarbouriech@google.comTor LattimoreGoogle DeepMindlattimore@google.comBrendan O’DonoghueGoogle DeepMindbodonoghue@google.comAbstractA popular perspective in Reinforcement learning (RL) casts the problem as prob...
A Comparison of Algorithms for Inference and Learning in Probabilistic Graphical Models Research into methods for reasoning under uncertainty is currently one of the most exciting areas of artificial intelligence, largely because it has recent... Frey, B.J,N Jojic - 《IEEE Transactions on Pattern ...
(i.e., hidden states in HMM) where each variable corresponds to a CpG site. Inference for each CR is made independently which enables the use of parallelization to lower computation time. We first describe the HMM for the one-grouping scenario (Additional File 1: Fig. S18a), as the ...
原文标题: Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Review 原文地址: https://arxiv.org/pdf/1805.00909.pdfarxiv.org/pdf/1805.00909.pdf 来自大佬Sergey Levine的综述性文章,刚接触强化学习时读过,那时候很多东西都不懂,当时以为这篇文章是教你如何按照概率图模型建模问题...