Reasoning about Epistemic Actions and Knowledge in Multi-Agent Systems Using Coq

In this paper, the authors outline a formal system for reasoning about agents＇ knowledge in knowledge games-a special type of multi-agent system. Knowledge games are card games where the agents＇ actions involve an exchange of information with other agents in the game. The authors＇ system is modeled using Coq-a formal proof management system. To the best of the authors＂ knowledge, there are no papers in which knowledge games are considered using a Coq proof assistant. The authors use the dynamic logic of common knowledge, where they particularly focus on the epistemic consequences of epistemic actions carried out by agents. The authors observe the changes in the system that result from such actions. Those changes that can occur in such a system that are of interest to the authors take the form of agents＇ knowledge about the state of the system, knowledge about other agents＇ knowledge, higher-order agents＇ knowledge and so on, up to common knowledge. Besides an axiomatic ofepistemic logic, the authors use a known axiomatization of card games that is extended with some new axioms that are required for the authors＇ approach. Due to a deficit in implementations grounded in theory that enable players to compute their knowledge in any state of the game, the authors show how the authors＇ approach can be used for these purposes.

Traditional agroecological knowledge and practices:The drivers and opportunities for adaptation actions in the northern region of Ghana

Agroecological practices are promoted as a more proactive approach than conventional agriculture to achieving a collective global response to climate change and variability while building robust and resilient agricultural systems to meet food needs and protect the integrity of ecosystems.There is relatively limited evidence on the key traditional agroecological knowledge and practices adopted by smallholder farmers,the factors that influence smallholder farmers’decision to adopt these practices,and the opportunities it presents for building resilient agricultural systems.Using a multi-scale mixed method approach,we conducted key informant interviews(n=12),focus group discussions(n=5),and questionnaire surveys(N=220)to explore the traditional agroecological knowledge and practices,the influencing factors,and the opportunities smallholder farmers presented for achieving resilient agricultural systems.Our findings suggest that smallholder farmers employ a suite of traditional agroecological knowledge and practices to enhance food security,combat climate change,and build resilient agricultural systems.The most important traditional agroecological knowledge and practices in the study area comprise cultivating leguminous crops,mixed crop-livestock systems,and crop rotation,with Relative Importance Index(RII)values of 0.710,0.708,and 0.695,respectively.It is reported that the choice of these practices by smallholder farmers is influenced by their own farming experience,access to market,access to local resources,information,and expertise,and the perceived risk of climate change.Moreover,the results further show that improving household food security and nutrition,improving soil quality,control of pest and disease infestation,and support from NonGovernmental Organizations(NGOs)and local authorities are opportunities for smallholder farmers in adopting traditional agroecological knowledge and practices for achieving resilient agricultural systems.The findings call into question the need for stakeholders and policy-makers at all levels to develop capacity and increase the awareness of traditional agroecological knowledge and practices as mechanisms to ensure resilient agricultural systems for sustainable food security.

Decision Tree and Naive Bayes Algorithm for Classification and Generation of Actionable Knowledge for Direct Marketing

Many companies like credit card, insurance, bank, retail industry require direct marketing. Data mining can help those institutes to set marketing goal. Data mining techniques have good prospects in their target audiences and improve the likelihood of response. In this work we have investigated two data mining techniques: the Naive Bayes and the C4.5 decision tree algorithms. The goal of this work is to predict whether a client will subscribe a term deposit. We also made comparative study of performance of those two algorithms. Publicly available UCI data is used to train and test the performance of the algorithms. Besides, we extract actionable knowledge from decision tree that focuses to take interesting and important decision in business area.

Agglomerative Approach for Identification and Elimination of Web Robots from Web Server Logs to Extract Knowledge about Actual Visitors

In this paper we investigate the effectiveness of ensemble-based learners for web robot session identification from web server logs. We also perform multi fold robot session labeling to improve the performance of learner. We conduct a comparative study for various ensemble methods (Bagging, Boosting, and Voting) with simple classifiers in perspective of classification. We also evaluate the effectiveness of these classifiers (both ensemble and simple) on five different data sets of varying session length. Presently the results of web server log analyzers are not very much reliable because the input log files are highly inflated by sessions of automated web traverse software’s, known as web robots. Presence of web robots access traffic entries in web server log repositories imposes a great challenge to extract any actionable and usable knowledge about browsing behavior of actual visitors. So web robots sessions need accurate and fast detection from web server log repositories to extract knowledge about genuine visitors and to produce correct results of log analyzers.

Multi-action-based approach for constructing knowledge map

To alleviate the information overload in the product design process,this work proposes a multiaction-based method for constructing knowledge map. Since the relationships of knowledge are implicit in the collected user activities,the method calculates the similarity according to the collected user activities.Three concepts,including knowledge,action and user,are explained first. Based on this,the similarity calculation method is illustrated in detail. The dependencies of actions and relations of the user are considered in the calculation method. Further,the approach of applying the constructed knowledge map to alleviate information overload is proposed. At last,the proposed method is validated by a knowledge search and result comparison experiment.

Is Knowledge Power?

Francis Bacon’s famous quote“knowledge is power,”has long been misunderstood,for his real intention was precisely to make humankind aware of the limitations of knowledge.His concept of potestas(power)is not about conquest,but about action,aiming to clarify the nature of knowledge,to get rid of the empty and shallow contemplation of antiquity,and thus to bring the spirit of the real world back to the earth,as Socrates did.Bacon emphasized the unity of knowledge and action while valuing action over knowledge.Nature in Bacon’s time was no longer sacred and was degraded to a poor substance that revealed its secrets after being tortured by scientific technology.As a result,natural teleology was completely abandoned.Bacon put man in increasing tension with nature,heralding Kant’s argument that human reason prescribed lawfulness to nature.But Bacon,after all,lived in an era not far from antiquity,so he agreed the limitations of knowledge and action and considered technology to be a labyrinth prone to divest one’s identity.Bacon thought that knowledge could be venom that made humankind swell,and the antidote was charity.Bacon’s quote is not so much an encouragement to take from nature as it is a way to learn from nature and to take a practical approach to happiness.

TwinNet: Twin Structured Knowledge Transfer Network for Weakly Supervised Action Localization

Action recognition and localization in untrimmed videos is important for many applications and have attracted a lot of attention. Since full supervision with frame-level annotation places an overwhelming burden on manual labeling effort, learning with weak video-level supervision becomes a potential solution. In this paper, we propose a novel weakly supervised framework to recognize actions and locate the corresponding frames in untrimmed videos simultaneously. Considering that there are abundant trimmed videos publicly available and well-segmented with semantic descriptions, the instructive knowledge learned on trimmed videos can be fully leveraged to analyze untrimmed videos. We present an effective knowledge transfer strategy based on inter-class semantic relevance. We also take advantage of the self-attention mechanism to obtain a compact video representation, such that the influence of background frames can be effectively eliminated. A learning architecture is designed with twin networks for trimmed and untrimmed videos, to facilitate transferable self-attentive representation learning. Extensive experiments are conducted on three untrimmed benchmark datasets (i.e., THUMOS14, ActivityNet1.3, and MEXaction2), and the experimental results clearly corroborate the efficacy of our method. It is especially encouraging to see that the proposed weakly supervised method even achieves comparable results to some fully supervised methods.

一种基于Subject-Action-Object三元组的知识基因提取方法

以专利引证网络为载体,从知识基因稳定性、遗传性以及变异性等基本特征出发,提出一种基于subject-action-object三元组的知识基因提取方法.应用连接度算法分析专利引证关系,挖掘引证专利和被引专利之间继承和发展的知识流,建立知识进化轨迹;利用文本语法分析技术,从专利权利要求书中提取subject-action-object三元组;基于语义词库WordNet进行语义加工,计算语义相似度,合并同义的subject-action-object三元组,绘制知识基因图谱.从美国专利数据库中采集了5 073项1975—1999年授权的数据挖掘领域的相关专利,分析了专利的地区分布情况和年度分布情况.从NBER(National Bureau of Economic Research)的专利数据集中查询得到专利引证关系,利用网络分析软件Pajek构建专利引证网络,作为实验数据样本,对所提出的知识基因提取方法进行验证.实验结果表明:所提取的subject-action-object三元组具备了知识基因稳定性、遗传性和变异性等特征,可以作为知识基因的一种表现形式.

企业协同知识管理工作流模型研究——基于action workflow方法

在借鉴问题解决导向的企业知识管理的过程描述基础上,指出企业协同知识管理过程是以协同知识库为核心的协同问题解决过程,并结合企业协同知识管理的工作流建模要求,论述了action work-flow工作流建模方法的特点,以及action workflow方法在企业协同知识管理中的应用。

非编码RNA与间充质干细胞研究的相关计量学分析

背景:非编码RNA作为一类不编码蛋白质的RNA分子,在细胞调控中发挥关键作用。同时,间充质干细胞具有多向分化潜能,对组织修复和再生至关重要。近年来,研究者们对非编码RNA在调控间充质干细胞功能中的作用展开了深入探讨。目的:通过文献计量学分析方法系统地了解非编码RNA与间充质干细胞相关研究的发展趋势与关键领域。方法:从Web of Science核心合集1990年至今的科学引文索引扩展获取非编码RNA与间充质干细胞相关研究的文献数据,运用VOSviewer和Cite Space计量学软件对年份、国家或地区、研究机构、被引文献和关键词进行发文量、聚类、被引频次、突增性和中介中心性进行分析,揭示该研究领域的知识基础及前沿热点。结果与结论:(1)最终纳入5348篇文献,发表在1997-2021年,相关文献呈现明显的增长趋势,尽管在2022年略有减少,其发文量仍保持较高水平,中国在该领域的研究中占据主导地位,其中上海交通大学为最活跃的机构。(2)对被引文献分析发现,高突增性、高中介中心性、高被引的文献主要与微小RNA、细胞外囊泡和骨代谢等内容相关,这些文献构成了非编码RNA与间充质干细胞研究领域的重要知识基础。(3)对关键词进行突增性分析发现,至今保持高突增性的关键词包括外泌体、环状RNA、细胞外囊泡和损伤。(4)对关键词进行聚类演变分析,发文量仍保持增长趋势的关键词聚类包括:肿瘤微环境、骨关节炎、氧化应激和细胞外囊泡,这些关键词反映了目前以及未来该领域的研究热点。(5)文章结果不仅展示了非编码RNA与间充质干细胞研究领域的研究态势,更重要的是有望为研究人员提供潜在的方向和启示。

基于CLIP模型和知识数据库的零样本动作识别

零样本动作识别旨在从已知类别的动作样本数据中学习知识,并将其迁移到未知的动作类别上,从而实现对未知动作样本的识别和分类.现有的零样本动作识别模型依赖有限的训练数据,可学习到的先验知识有限,难以将视觉特征准确地映射到语义标签上,是限制零样本学习性能提升的关键因素.针对上述问题,本文提出了一种引入外部知识数据库和CLIP模型的零样本学习框架,利用多模态CLIP模型通过自监督对比学习方式积累的知识,来扩充零样本动作识别模型的先验知识.同时,设计了时序编码器,以弥补CLIP模型时序建模能力的欠缺.为了使模型学习到更丰富的语义特征,缩小视觉特征和语义标签之间的语义鸿沟,本文扩展了已知动作类别的语义标签,用更为详细的描述语句代替简单的文本标签,丰富了文本表示的语义信息;在此基础上,在模型外部构建了一个知识数据库,在不增加模型参数规模的条件下为模型提供额外的辅助信息,强化视觉特征与文本特征表示之间的关联关系.最后,本文遵循零样本学习规范,对模型进行微调,使其适应零样本动作识别任务,提高了模型的泛化能力.所提方法在HMDB51和UCF101两个主流数据集上进行了广泛实验,实验数据表明,该方法的识别性能相比目前的先进方法在上述两个数据集上分别提升了3.8%和2.3%,充分体现了所提方法的有效性.

阳明心学中的道德知识与道德动机——从“良知发用”的角度看

基于比较哲学视野的分析,王阳明的知行合一论题的解释在传统中包含着三种不同路径的理解,即形而上学论题、知识论论题和元伦理学论题。致良知学说体现了知行合一的三种路径理解的统一,其中道德知识和道德动机的关系是把握知行合一与致良知学说的关键。本文把心学工夫论理解为道德意识的自我展开和实现,通过论证良知发用的功能,阐明阳明心学中包含着近似于内在主义道德动机的混合模型,并由此产生奠基于道德感知和道德情感交互性的美德伦理论述。

活动理论视角下游戏化学习中知识转移活动的特征及运行过程研究

[研究目的]将活动理论引入游戏化学习的知识转移活动中,系统性推动游戏化学习中知识转移活动中各要素的高效协作,加快知识转移与共享,促进知识增值和创新。[研究方法]基于活动理论特质和知识特征确定游戏化学习中知识转移特征,并构建知识转移活动模型,以明确各要素的协调交互对知识转移效果的作用,最后以博物馆知识剧本杀为例,验证结论。[研究结论]活动理论能够明确知识转移的运行过程,可以应用于具体活动的显隐性知识转移分析,研究发现活动中的矛盾、游戏内容、技术赋能、共同体的互动和游戏情境对主体的知识转移效果产生显著影响。

“知行合一”视域下大型体育赛事风险防范研究之审视

安全是发展的前提,大型体育赛事风险防范是建设体育强国的基本要求。本文采用文献资料法、逻辑分析法等研究方法,依托知行合一的哲学思想,深入剖析了“知”与“行”分别在大型体育赛事风险防范中的理论旨归与实践内涵,同时借助风险案例对大型体育赛事风险防范中知行割裂的失范后果进行了探索,进一步阐释大型体育赛事风险防范工作中知行合一的必要性。大型体育赛事风险防范需要知行合一,这是其既有的研究逻辑、理论内在逻辑与现实实践逻辑共同规定下的必由之路,亦即在“知”的指导下开展大型体育赛事风险的管理实践,同时在“行”的实践情境中不断推进对于“知”的深化,从而实现对于大型体育赛事风险防范工作的本体论、认识论与方法论的统一。

教育家精神引领下“双师型”教师自主发展路径探索——王阳明“知行合一”思想的当代启示

教育家精神是引领职教教师专业发展的崇高精神内核,是职业教育培养大国工匠、高技能人才的关键。“双师型”教师所强调的理论与实践相结合的理念以及“双师型”教师自主专业发展中的“教师主体性”与王阳明的“知行合一”思想具有高度一致性。运用王阳明“知行合一”思想,对当前“双师型”教师自我专业发展中存在的专业信念缺失、主体动力不足、学用知行脱节、反省反思不足、教学智慧缺乏等问题进行归因;在王阳明思想中“为己-克己-成己”的个人成长进路的启示下,探索出“双师型”教师“志业-敬业-乐业”的自我专业发展进路,形成以“立志为先”铸就信念之魂、以“心之本体”激活主体动力、以“知行一体”提升理实结合能力、以“省察克治”践行自我革命精神、以“事上磨练”促进职教智慧生成、以“万物一体”心境引领职教发展,完成教育家型职教教师自我实现的专业发展路径。

知行合一的教学方法在医学生心肺复苏技能培训中的应用研究

目的:探讨知行合一的教学方法在医学生心肺复苏技能培训中的应用效果。方法:选取山西科大学临床医学5+3一体化医学生108人作为研究对象,2018级为对照组,2020级为观察组,每组54人。对照组采用传统教学方法进行心肺复苏技能培训,观察组采用知行做合一的教学方法进行培训,通过对比两组理论和技能测试成绩,评估知行合一的教学方法的满意度及培训效果。结果:观察组理论测试成绩和技能成绩均高于对照组,差异有统计学意义(P<0.05)。观察组培训效果(心肺复苏实践操作能力和参加心肺复苏急救的信心)明显高于对照组,差异有统计学意义(P<0.05)。在问卷调查中,观察组满意度高于对照组,差异有统计学意义(P<0.05)。结论:知行合一教学方法在急诊心肺复苏教学中具有显著的应用效果,能够提高学生的学习成绩和教学满意度。

中国知行统一观的历史演进及其教育学意义

作为中华优秀传统文化和教育思想重要内容之一的知行统一观,经历了一百多年的现代化历程。这一百年多年的现代化过程,主要是传统知行合一观的马克思主义化过程。知行统一观的这一转化,给教育的理论和实践带来了新变化。在新时代,重视个人道德体悟和践履的中国传统知行统一观与毛泽东以来的以社会实践为基础、以社会理想建构为终极目的的马克思主义知行统一观再次结合起来,从历史的角度来看,这正是正反合的辩证发展过程。

地方性知识如何参与乡村媒介行动:“土味”短视频传播的人类学考察

人类学有关地方性知识的论说,以“情境”“特定”“专属”等特征与前现代/传统社会的特定时空、地方和人群相联系。在传媒技术、话语生态快速迭代的当前社会语境下,众多“土味”短视频凭借低门槛、高弥散的媒介技术属性全面介入日常生活,也在中国城乡关系的重构过程中拓展了地方性知识嵌入媒介社会行动的新讨论空间。本研究凸显媒介空间地方性知识的实践面向,基于一个西北乡村媒介生活图景的民族志深描,从符号人类学视域出发考察乡村日常生活的符号化与媒介化的具身实践,观照“刷”短视频这一微观身体操演中隐含的知识平权、信息扁平和基层主体身份意识的建构和表达,从而在媒介符号“可见性”“可供性”与“可刷性”的复杂关联中看到,地方性知识不仅作为一种知识要素嵌入了“土味”乡村的媒介符号图景,也作为重要的行动路径折射出乡村民众从“地方”这一特定历史位置参与当下媒介世界的复杂经验和主体意义。

高校文化育人现状及优化策略探析

作为国家和民族的根本特征和精神家园,文化是国家软实力毋庸置疑的核心内容,既肩负着汇聚民族力量的重任,也是综合国力的重要构成要素。文化育人的主旨在于通过优秀文化传统和现代教育手段,引领民众确立正确的价值观念,提升自身人文素养,塑造健康人格。作为致力于立德树人的文化组织,高校更应充分发挥自身优势,将文化育人列为思想政治教育的关键举措,真正实现以文化人,以文育人。本文尝试就高校文化育人内涵、特征、存在问题及改进方法等问题进行梳理与阐述。