Two timescale stochastic approximation (SA) has been widely used in value-based reinforcement learning algorithms. In the policy evaluation setting, it can model the linear and nonlinear temporal difference learning with gradient correction (TDC) algorithms as linear SA and nonlinear SA, respectively....
Below is the taxonomy of reinforcement learning algorithms. Solid line indicates some progression from one idea to another. Dashed line indicates a loose connection. On the bottom you can see the timeline of the publication year of the algorithms....
In recent years, reinforcement learning (RL) systems have shown impressive performance and remarkable achievements. Many achievements can be attributed to combining RL with deep learning. However, those systems lack explainability, which refers to our understanding of the system’s decision-making process...
A non-exhaustive, but useful taxonomy of algorithms in modern RL 上图是现代RL模型一个大致的分类(2018年)。 在强化学习模型层出不穷的今天,在一个简短的介绍文章里选择这一领域最有价值的模型是个令人头疼的问题。为了在有限的篇幅中方便读者们吸收内容,我们舍弃了一些相对先进的模型与方法, 如强化学习中的...
基于正则化的图自编码器在推荐算法中的应用 Application of graph auto-encoders based on regularization in recommendation algorithms2024-04-1113.用余弦相似度修正评分的协同过滤推荐算法2024-04-1114.基于标签值分布的强化学习推荐算法(Reinforcement Learning Recommendation Algorithm Based on Label Value Distribution)...
IoT is one of the fastest-growing technologies and it is estimated that more than a billion devices would be utilised across the globe by the end of 2030. To maximise the capability of these connected entities, trust and reputation among IoT entities is
With the development of deep learning algorithms and computer hardware, advances have been made in sence image translation [209–212], remote sensing image caption [213–215], etc. While cross-modal translation is an emerging task in remote sensing, an extensive range of algorithms have been ...
We also review the most outstanding papers by category and the strategies and algorithms proposed for the most relevant activities: batching, routing, sequencing, waiting, and assigning. To conclude, we outline the open issues and future paths of the topic under study....
[23] Survey of offloading algorithms MCC and MEC Algorithms [24] Survey of multiobjective decision-making frameworks MCC Multiobjective frameworks This study Survey of MEC and MCC offloading frameworks MCC and MEC Computing environments, optimization scenarios, and granularity We present the following no...
In: Mobile Computing and Sustainable Informatics: Proceedings of ICMCSI 2021. Springer; p. 65–94 Ren J, Xia F, Lee I, Hoshyar AN, Aggarwal CC (2023) Graph Learning for Anomaly Analytics: Algorithms, Applications, and Challenges. ACM Trans Intell Syst Technol. 14(2):28:1-28:29 Article...