检索结果-南通市图书馆

An Empirical Study on Google Research Football Multi-agent Scenarios

Machine intelligence Research 2024年第3期21卷 549-570页

作者： Yan Song He Jiang Zheng Tian Haifeng Zhang Yingping Zhang Jiangcheng Zhu Zonghong Dai Weinan Zhang Jun Wang Institute of Automation Chinese Academy of SciencesBeijing100190China Digital Brain Lab Shanghai200001China shanghaiTech University Shanghai200001China Huawei Cloud Guiyang550003China shanghai Jiao Tong University Shanghai200001China University college London LondonWC1E 6PTUK

Few multi-agent reinforcement learning (MARL) researches on Google research football (GRF) focus on the 11-vs-11 multi-agent full-game scenario and to the best of our knowledge, no open benchmark on this scenario has been released to the public. In this work, we fill the gap by providing a population-based MARL training pipeline and hyperparameter settings on multi-agent football scenario that outperforms the bot with difficulty 1.0 from scratch within 2 million steps. Our experiments serve as a reference for the expected performance of independent proximal policy optimization (IPPO), a state-of-the-art multi-agent reinforcement learning algorithm where each agent tries to maximize its own policy independently across various training configurations. Meanwhile, we release our training framework Light-MALib which extends the MALib codebase by distributed and asynchronous implementation with additional analytical tools for football games. Finally, we provide guidance for building strong football AI with population-based training and release diverse pretrained policies for benchmarking. The goal is to provide the community with a head start for whoever experiment their works on GRF and a simple-to-use population-based training framework for further improving their agents through self-play. The implementation is available at https://***/shanghai-Digital-Brain-Laboratory/DB-Football.

关键词： Multi-agent reinforcement learning(RL) distributed RL system population-based training reward shaping game theory

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Promoting interactions between cognitive science and large language models

引用

The Innovation 2024年第2期5卷 9-10页

作者： Youzhi Qu Penghui Du Wenxin Che Chen Wei Chi Zhang Wanli Ouyang Yatao Bian Feiyang Xu Bin Hu Kai Du Haiyan Wu Jia Liu Quanying Liu Department of Biomedical Engineering Southern University of Science and TechnologyShenzhen 518055China shanghai AI Laboratory Shanghai 200232China Tencent AI Lab Shenzhen 518057China iFLYTEK AI Research Hefei 230088China School of Medical Technology Beijing Institute of TechnologyBeijing 100081China Institute for Artificial intelligence Peking UniversityBeijing 100871China Centre for cognitive and Brain Sciences and Department of Psychology University of MacaoMacao 999078China Department of Psychology Tsinghua UniversityBeijing 100084China

Large language models(LLMs)have made unprecedented progress,demonstrating human-like language proficiency and an extraordinary ability to encode complex *** emergence of high-level cognitive capabilities in LLMs,such as in-context learning and complex reasoning,suggests a path toward the realization of artificial general intelligence(AGI).However,we lack scientific theories and tools to assess and interpret such an emergence of the advanced intelligence of *** intelligence(AI)has been extensively applied in various areas of fundamental science to accelerate scientific research.

关键词： cognitive such language

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Training Generative Adversarial Networks with Adaptive composite Gradient

引用

Data intelligence 2024年第1期6卷 120-157页

作者： Huiqing Qi Fang Li Shengli Tan Xiangyun Zhang School of Mathematical Sciences East China Normal UniversityShanghai 200241China

The wide applications of Generative adversarial networks benefit from the successful training methods,guaranteeing that an object function converges to the local ***,designing an efficient and competitive training method is still a challenging task due to the cyclic behaviors of some gradient-based ways and the expensive computational cost of acquiring the Hessian *** address this problem,we proposed the Adaptive composite Gradients(ACG)method,linearly convergent in bilinear games under suitable *** analysis and toy-function experiments both suggest that our approach alleviates the cyclic behaviors and converges faster than recently proposed SOTA *** convergence speed of the ACG is improved by 33%than other *** ACG method is a novel Semi-Gradient-Free algorithm that can reduce the computational cost of gradient and Hessian by utilizing the predictive information in future *** mixture of Gaussians experiments and real-world digital image generative experiments show that our ACG method outperforms several existing technologies,illustrating the superiority and efficacy of our method.

关键词： Generative adversarial networks adaptive composite gradient semi-gradient free game theory bilinear game

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Knowledge enhanced graph inference network based entity-relation extraction and knowledge graph construction for industrial domain

引用

Frontiers of Engineering Management 2024年第1期11卷 143-158页

作者： Zhulin HAN Jian WANG college of Electronic and Information Engineering Tongji UniversityShanghai 200092China

With the escalating complexity in production scenarios, vast amounts of production information are retained within enterprises in the industrial domain. Probing questions of how to meticulously excavate value from complex document information and establish coherent information links arise. In this work, we present a framework for knowledge graph construction in the industrial domain, predicated on knowledge-enhanced document-level entity and relation extraction. This approach alleviates the shortage of annotated data in the industrial domain and models the interplay of industrial documents. To augment the accuracy of named entity recognition, domain-specific knowledge is incorporated into the initialization of the word embedding matrix within the bidirectional long short-term memory conditional random field (BiLSTM-CRF) framework. For relation extraction, this paper introduces the knowledge-enhanced graph inference (KEGI) network, a pioneering method designed for long paragraphs in the industrial domain. This method discerns intricate interactions among entities by constructing a document graph and innovatively integrates knowledge representation into both node construction and path inference through TransR. On the application stratum, BiLSTM-CRF and KEGI are utilized to craft a knowledge graph from a knowledge representation model and Chinese fault reports for a steel production line, specifically SPOnto and SPFRDoc. The F1 value for entity and relation extraction has been enhanced by 2% to 6%. The quality of the extracted knowledge graph complies with the requirements of real-world production environment applications. The results demonstrate that KEGI can profoundly delve into production reports, extracting a wealth of knowledge and patterns, thereby providing a comprehensive solution for production management.

关键词： knowledge graph construction industrial BiLSTM-CRF document-level relation extraction graph inference

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Optimizing prediction models for pancreatic fistula after pancreatectomy:Current status and future perspectives

引用

World Journal of Gastroenterology 2024年第10期30卷 1329-1345页

作者： Feng Yang John A Windsor De-Liang Fu Department of Pancreatic Surgery Huashan HospitalShanghai Medical CollegeFudan UniversityShanghai 200040China Surgical and Translational Research Centre Faculty of Medical and Health SciencesUniversity of AucklandAuckland 1142New Zealand

Postoperative pancreatic fistula(POPF)is a frequent complication after pancre-atectomy,leading to increased morbidity and *** prediction models for POPF has emerged as a critical focus in surgical *** over sixty models following pancreaticoduodenectomy,predominantly reliant on a variety of clinical,surgical,and radiological parameters,have been documented,their predictive accuracy remains suboptimal in external validation and across diverse *** models after distal pancreatectomy continue to be pro-gressively reported,their external validation is eagerly ***,POPF prediction after central pancreatectomy is in its nascent stage,warranting urgent need for further development and *** potential of machine learning and big data analytics offers promising prospects for enhancing the accuracy of prediction models by incorporating an extensive array of variables and optimizing algorithm ***,there is potential for the development of personalized prediction models based on patient-or pancreas-specific factors and postoperative serum or drain fluid biomarkers to improve accuracy in identifying individuals at risk of *** the future,prospective multicenter studies and the integration of novel imaging technologies,such as artificial intelligence-based radiomics,may further refine predictive *** these issues is anticipated to revolutionize risk stratification,clinical decision-making,and postoperative management in patients undergoing pancre-atectomy.

关键词： Pancreatic fistula Pancreaticoduodenectomy Distal pancreatectomy Central pancreatectomy Prediction model Machine learning Artificial intelligence

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Multi-granularity feature enhancement network for maritime ship detection

引用

CAAI Transactions on intelligence Technology 2024年第3期9卷 649-664页

作者： Li Ying Duoqian Miao Zhifei Zhang Hongyun Zhang Witold Pedrycz Department of computer Science and Technology Tongji UniversityShanghaiChina Project Management Office of China National Scientific Seafloor Observatory Tongji UniversityShanghaiChina Department of Electrical and computer Engineering AlbertaEdmontonCanada System Research Institute Polish Academy of SciencesWarsawPoland

Due to the characteristics of high resolution and rich texture information,visible light images are widely used for maritime ship ***,these images are suscep-tible to sea fog and ships of different sizes,which can result in missed detections and false alarms,ultimately resulting in lower detection *** address these issues,a novel multi-granularity feature enhancement network,MFENet,which includes a three-way dehazing module(3WDM)and a multi-granularity feature enhancement module(MFEM)is *** 3WDM eliminates sea fog interference by using an image clarity automatic classification algorithm based on three-way decisions and FFA-Net to obtain clear image ***,the MFEM improves the accuracy of detecting ships of different sizes by utilising an improved super-resolution reconstruction con-volutional neural network to enhance the resolution and semantic representation capa-bility of the feature maps from *** results demonstrate that MFENet surpasses the other 15 competing models in terms of the mean Average Pre-cision metric on two benchmark datasets,achieving 96.28%on the McShips dataset and 97.71%on the SeaShips dataset.

关键词： object classification object recognition rough sets rough set theory

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Knowledge-embedded spatio-temporal analysis for euploidy embryos identification in couples with chromosomal rearrangements

引用

Chinese Medical Journal 2024年第6期137卷 694-703页

作者： Fangying Chen Xiang Xie Du Cai Pengxiang Yan Chenhui Ding Yangxing Wen Yanwen Xu Feng Gao Canquan Zhou Guanbin Li Qingyun Mai Reproductive Medicine Center The First Affiliated Hospital of Sun Yat-sen UniversityGuangzhouGuangdong 510080China Guangdong Provincial Key Laboratory of Reproductive Medicine GuangzhouGuangdong 510080China School of computer Science and Engineering Sun Yat-sen UniversityGuangzhouGuangdong 510006China Department of General Surgery(colorectal Surgery) The Sixth Affiliated Hospital of Sun Yat-sen UniversityGuangzhouGuangdong 510655China Guangdong Provincial Key Laboratory of colorectal and Pelvic Floor Diseases The Sixth Affiliated HospitalSun Yat-sen UniversityGuangzhouGuangdong 510655China Biomedical Innovation Center The Sixth Affiliated HospitalSun Yat-sen UniversityGuangzhouGuangdong 510655China shanghai Artificial intelligence Laboratory Shanghai 200232China

Background:The goal of the assisted reproductive treatment is to transfer one euploid blastocyst and to help infertile women giving birth one healthy *** algorithms have been used to assess the ploidy status of embryos derived from couples with normal chromosome,who subjected to preimplantation genetic testing for aneuploidy(PGT-A)***,it is currently unknown whether artificial intelligence model can be used to assess the euploidy status of blastocyst derived from populations with chromosomal ***:From February 2020 to May 2021,we collected the whole raw time-lapse videos at multiple focal planes from in vitro cultured embryos,the clinical information of couples,and the comprehensive chromosome screening results of those blastocysts that had received PGT ***,we developed a novel deep learning model called the Attentive Multi-Focus Selection Network(AMSNet)to analyze time-lapse videos in real time and predict blastocyst *** upon AMSNet,we integrated additional clinically predictive variables and created a second deep learning model,the Attentive Multi-Focus Video and Clinical Information Fusion Network(AMCFNet),to assess the euploidy status of *** efficacy of the AMCFNet was further tested in embryos with parental chromosomal *** receiver operating characteristic curve(ROC)was used to evaluate the superiority of the ***:A total of 4112 embryos with complete time-lapse videos were enrolled for the blastocyst formation prediction task,and 1422 qualified blastocysts received PGT-A(n=589)or PGT for chromosomal structural rearrangement(PGT-SR,n=833)were enrolled for the euploidy assessment task in this *** AMSNet model using seven focal raw time-lapse videos has the best real-time *** real-time accuracy for AMSNet to predict blastocyst formation reached above 70%on the day 2 of embryo culture,and then increased to 80%on the day 4 of embryo ***

关键词： Euploidy status Embryo Time-lapse imaging Deep learning Spatio-temporal analysis Preimplantation genetic testing for chromosomal structural rearrangement

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Guest editorial:Special Issue on Artificial intelligence and Emerging computational Approaches for Tribology

引用

Friction 2024年第6期12卷 1057-1059页

作者： Zhinan ZHANG Shuaihang PAN Bart RAEYMAEKERS State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong UniversityShanghai 200240China Department of Mechanical Engineering University of UtahSalt Lake CityUT 84112USA Department of Mechanical Engineering Virginia TechBlacksburgVA 24061USA

Tribo-behavior is a complex system-based time-dependent process,and it is difficult to accurately model a tribo-system and predict its ***,tribology research,in most cases,has relied on extensive *** by the artificial intelligence(AI)-for-science revolution,AI and other emerging computational approaches provide opportunities to explore the complex processes in tribo-systems and the physical mechanisms of tribo-behavior in an efficient way,significantly pushing the boundaries of tribology research.

关键词： behavior editorial artificial

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Distributed Optimal Variational GNE Seeking in Merely Monotone Games

引用

IEEE/CAA Journal of Automatica Sinica 2024年第7期11卷 1621-1630页

作者： Wangli He Yanzhen Wang IEEE the Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of EducationEast China University of Science and TechnologyShanghai 200237China

In this paper, the optimal variational generalized Nash equilibrium(v-GNE) seeking problem in merely monotone games with linearly coupled cost functions is investigated, in which the feasible strategy domain of each agent is coupled through an affine constraint. A distributed algorithm based on the hybrid steepest descent method is first proposed to seek the optimal v-GNE. Then, an accelerated algorithm with relaxation is proposed and analyzed, which has the potential to further improve the convergence speed to the optimal v-GNE. Some sufficient conditions in both algorithms are obtained to ensure the global convergence towards the optimal v-GNE. To illustrate the performance of the algorithms, numerical simulation is conducted based on a networked Nash-cournot game with bounded market capacities.

关键词： Distributed algorithms equilibria selection generalized Nash equilibrium(GNE) merely monotone games

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Digital Transformation:The Impact of e-CNY on Securities Institutions and Financial Systems in China

引用

Proceedings of Business and Economic Studies 2024年第2期7卷 38-45页

作者： Xinyue Mei shanghai University Shanghai 200444China

In recent years,the rapid advancement of emerging technologies such as big data,blockchain,and artificial intelligence has accelerated the transformation of currencies,shifting from materialization towards digitization and *** e-CNY stands out as a prime example of China’s pioneering digital financial innovation *** by the central bank,it embodies the national *** the e-CNY’s application field and reach expand,its relationship with the financial market grows increasingly *** a significant participant in China’s financial landscape and a proactive responder to national policies,the securities industry is profoundly influenced by the e-CNY across various ***,this paper undertakes a theoretical analysis of the e-CNY’s implementation within securities institutions,concluding that it will usher in a new paradigm for the entire financial system.

关键词： e-CNY Securities institutions Digital transformation

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：