Because these methods fail to distinguish the most relevant historical courses, which can contribute to predicting the target course that indeed reflects the user's interests from her sequential learning behaviors. In this paper, we propose a context-aware reinforcement learning method, named ...
Context-Aware Adaptive Route Mutation Scheme:A Reinforcement Learning Approach 【论文阅读】基于强化学习的上下文感知的自适应路由变异方案 1. 摘要 1.1 问题背景 移动目标防御(MTD)是一种新兴的主动防御技术,可以降低漏洞被攻击的风险。MTD技术介绍:使攻击面动态化,而不是通过监测,预防,监视,跟踪或补救威胁来防御不...
reinforcement learningsingle‐agentReinforcement learning (RL) is utilized in a wide range of real﹚orld applications. Typical applications include single agent‐based RL. However, most practical tasks require multiple agents for cooperative control processes. Multiple゛gent RL demands complicated design, ...
Context-aware Dynamics Model for Generalization in Model-Based Reinforcement Learning 发表时间:2020(ICML 2020) 文章要点:这篇文章想说model based方法在data efficiency和planning方面都具有天然优势,但是model的泛化性通常是个问题。这篇文章提出学一个context相关的latent vector,然后用model去predict的时候会基于这个...
Context-Aware Sparse Deep Coordination Graphsarxiv.org/abs/2106.02886 背景介绍 这篇文章从标题就可以看出来,是利用图结构来解决MARL问题的。这类文章相比其他fully decentralized的MARL工作,主要的出发点是那些方法中每个智能体的utility function(就是Q函数)仅依赖自己的观测和动作,可能无法区分出其他智能体对自己...
Context-aware Dynamics Model for Generalization in Model-Based Reinforcement Learning 发表时间:2020(ICML 2020) 文章要点:这篇文章想说model based方法在data efficiency和planning方面都具有天然优势,但是model的泛化性通常是个问题。这篇文章提出学一个context相关的latent vector,然后用model去predict的时候会基于这个...
In this paper we present our context-aware hierarchical reinforcement learning scheme, which significantly improves accuracy of symptom checking over traditional systems while also making a limited number of inquiries. 展开 会议名称: Proceedings of the Thirty-Second AAAI Conference on Artificial ...
CONTEXT-aware computingREINFORCEMENT learningPHYSIOLOGICAL adaptationBUDGETMETAHEURISTIC algorithmsALGORITHMSIn pervasive systems, context is a direct cause to adapt ... Z Laboudi,A Moudjari,A Saighi,... - 《Neural Computing & Applications》 被引量: 0发表: 2022年 加载更多研究...
In view of the problems of severe access conflicts, high queue backlog, and low energy efficiency in the massive terminal access scenario of the power Internet of things (power IoT) in 6G era, a context-aware learning-based access control (CLAC) algorithm ...
Then, our goal is to use the context-aware expert data to learn an optimal context-unaware policy for the learner using only a few new data samples. Such problems are typically solved using imitation learning that assumes that both the expert and learner agents have access to the same ...