• Title/Summary/Keyword: small world network

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Reinforcement Learning with Small World Network (복잡계 네트워크를 이용한 강화 학습 구현)

  • 이승준;장병탁
    • Proceedings of the Korean Information Science Society Conference
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    • 2004.10a
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    • pp.232-234
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    • 2004
  • 강화 학습(Reinforcement Learning)을 실제 문제에 적용하는 데 있어 가장 큰 문제는 차원성의 저주(Curse of dimensionality)이다. 문제가 커짐에 따라 목적을 이루기 위해서 더 않은 단계의 판단이 필요하고 이에 따라 문제의 해결이 지수적으로 어려워지게 된다. 이를 해결하기 위칠 문제를 여러 단계로 나누어 단계별로 학습하는 계층적 강화 학습(Hierarchical Reinforcement Learning)이 제시된 바 있다. 하지만 대부분의 계층적 강화 학습 방법들은 사전에 문제의 구조를 아는 것을 전제로 하며 큰 사이즈의 문제를 간단히 표현할 방법을 제시하지 않는다. 따라서 이들 방법들도 실제적인 문제에 바로 적용하기에는 적합하지 않다. 이러한 문제점들을 해결하기 위해 복잡계 네트워크(Complex Network)가 갖는 작은 세상 성질(Small world Property)에 착안하여 자기조직화 하는 생장 네트워크(Self organizing growing network)를 기반으로 한 환경 표현 모델이 제안된 바 있다. 이러한 모델에서는 문제 크기가 커지더라도 네트워크의 사이즈가 크게 커지지 않기 때문에 문제의 난이도가 크기에 따라 크게 증가하지 않을 것을 기대할 수 있다. 본 논문에서는 이러한 환경 모델을 사용한 강화 학습 알고리즘을 구현하고 실험을 통하여 각 모델이 강화 학습의 문제 사이즈에 따른 성능에 끼치는 영향에 대해 알아보았다.

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Building Disaster Communication Network to Protect Foreign Knowledge Workers from Disasters (외국인 지식노동자 보호를 위한 재난통신 네트워크 구축에 관한 개념적 연구)

  • Oh, Nam-Kyung
    • The Journal of the Korea Contents Association
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    • v.22 no.2
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    • pp.107-115
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    • 2022
  • This study discusses how to protect foreign knowledge workers from disasters conceptually. While their prestigious social and economic status, the knowledge workers can become vulnerable to disasters due to their nomadic lifestyle and voluntary isolation from communities where they reside temporarily. This study introduced and discussed strengths and weaknesses of various types of disaster communication networks and found the Small World Network (SWN) and the use of structural holes would be an appropriate strategy for the protection of knowledge workers. The use of mediators for disaster communication would be a strategic intervention from public and private organizations since that addresses voluntary isolation issue without restructuring existing disaster communication network.

Analysis on structure of National Innovation System in IT (IT분야 국가혁신시스템 네트워크 구조 분석)

  • Ju, Seong-Hwan
    • Journal of Digital Convergence
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    • v.14 no.4
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    • pp.129-138
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    • 2016
  • This study was conducted with the network-related viewpoint to see the aspect of interaction among innovation factors of this country's national innovation system in information and communication sector. For this, the relations in which institutions have conducted a joint study of national R&D projects supported by the government were analyzed by the method of Social Network Analysis. As a result of the analysis, the network of national innovation system in information and communication sector of this country turned out to be "small world network." Based on the result, it was found out that innovation subjects in the sector of this country closely exchange knowledge and information. In addition, among innovation subjects in the network, the proportion of research institutions was relatively high and the proportion of enterprises was relatively low, which confirmed that the activity for technical innovation has been made under the lead of the government. Further study is required to find out what effect the network structure of national innovation system has on the success of innovation.

An Analysis on the Web Usage Pattern Graph Using Web Users' Access Information (웹 이용자의 접속 정보 분석을 통한 웹 활용 그래프의 구성 및 분석)

  • Kim, Hu-Gon;Kim, Jae-Gyo
    • Korean Management Science Review
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    • v.23 no.3
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    • pp.63-75
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    • 2006
  • There are many kinds of research on web graph, most of them are focus on the hyperlinked structure of the web graph. Well known results on the web graph are rich-get-richer phenomenon, small-world phenomenon, scale-free network, etc. In this paper, we define 3 new directed web graph, so called the Web Usage Pattern Graph (WUPG), that nodes represent web sites arid arcs between nodes represent a movement between two sites by users' browsing behavior. The data to constructing the WUPG, approximately 56,000 records, are gathered from some users' PCs. The results analysing the data summarized as follows : (i) extremely rich-get-richer phenomenon (ii) average path length between sites is significantly less than the previous one (iii) less external hyperlinks, more internal hyperlinks.

Studying Structural Evaluation of Web Link Structure and Performance in Destination Marketing Organizations (웹링크 구조와 웹사이트 성과간의 구조적 평가에 관한 연구: 컨벤션비지터뷰로(CVB)를 대상으로)

  • Joun, Hyo-Jae;Cho, Nam-Jae
    • Journal of Digital Convergence
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    • v.5 no.2
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    • pp.91-98
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    • 2007
  • Destination marketing organizations (DMO) have been building up the cyber city in the WWW. Website for DMO is a core channel to promote regional attractions. This research suggests the issue of criteria for evaluating DMO's performance in the Internet. The method of evaluation focuses on the structure in perspective of linkage based on small world theory and direct network. Convention & Visitors & Bureau (CVB) in tourism and travel industry playa role to promote and held the international meeting and exhibitions. CVB's websites evaluated according to web link structure and performance.

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Random Generation of the Social Network with Several Communities

  • Huh, Myung-Hoe;Lee, Yong-Goo
    • Communications for Statistical Applications and Methods
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    • v.18 no.5
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    • pp.595-601
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    • 2011
  • A community of the social network refers to the subset of nodes linked more densely among them than to others. In this study, we propose a Monte-Carlo method for generating random social unipartite and bipartite networks with two or more communities. Proposed random networks can be used to verify the small world phenomenon of the social networks with several communities.

Analysis of the World Religions Based on Network (네트워크 기반 세계종교 분석)

  • Kim, Hak Yong
    • The Journal of the Korea Contents Association
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    • v.22 no.6
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    • pp.24-34
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    • 2022
  • Viewing religion as contents, we analyzed the network structure by creating networks on 13 world religions. The whole network was constructed by combining 13 religions, and it showed the characteristics of a scale-free network as a general social network. The world religion network had a very small value of clustering coefficient, unlike the general social network. This seems to be the result of the diversity of terms that describe religion. The core network was constructed by applying K-core algorithm used to create the core network to the whole network. When k-3 was applied, it was too complicated but when k-4 was applied, it was too simple to obtain meaningful results. It indicates that it difficult to apply the K-core algorithm to a network containing a low clustering coefficient. Therefore, core networks were constructed according to the number of key words centered on the hub node to analyze the characteristics of world religions. In addition, meaningful information was derived by constructing the world's five major religious networks and East Asian religious networks. In this study, various information was obtained by analyzing world religions as contents. It was also presented a method of creating and analyzing a core network based on key words for networks with a low clustering coefficient.

Properties of a Social Network Topology of Livestock Movements to Slaughterhouse in Korea (도축장 출하차량 이동의 사회연결망 특성 분석)

  • Park, Hyuk;Bae, Sunhak;Pak, Son-Il
    • Journal of Veterinary Clinics
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    • v.33 no.5
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    • pp.278-285
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    • 2016
  • Epidemiological studies have shown the association between transportation of live animals and the potential transmission of infectious disease between premises. This finding was also observed in the 2014-2015 foot-and-mouth disease (FMD) outbreak in Korea. Furthermore, slaughterhouses played a key role in the global spread of the FMD virus during the epidemic. In this context, in-depth knowledge of the structure of direct and indirect contact between slaughterhouses is paramount for understanding the dynamics of FMD transmission. But the social network structure of vehicle movements to slaughterhouses in Korea remains unclear. Hence, the aim of this study was to configure a social network topology of vehicle movements between slaughterhouses for a better understanding of how they are potentially connected, and to explore whether FMD outbreaks can be explained by the network properties constructed in the study. We created five monthly directed networks based on the frequency and chronology of on- and off-slaughterhouse vehicle movements. For the monthly network, a node represented a slaughterhouse, and an edge (or link) denoted vehicle movement between two slaughterhouses. Movement data were retrieved from the national Korean Animal Health Integrated System (KAHIS) database, which tracks the routes of individual vehicle movements using a global positioning system (GPS). Electronic registration of livestock movements has been a mandatory requirement since 2013 to ensure traceability of such movements. For each of the five studied networks, the network structures were characterized by small-world properties, with a short mean distance, a high clustering coefficient, and a short diameter. In addition, a strongly connected component was observed in each of the created networks, and this giant component included 94.4% to 100% of all network nodes. The characteristic hub-and-spoke type of structure was not identified. Such a structural vulnerability in the network suggests that once an infectious disease (such as FMD) is introduced in a random slaughterhouse within the cohesive component, it can spread to every other slaughterhouse in the component. From an epidemiological perspective, for disease management, empirically derived small-world networks could inform decision-makers on the higher potential for a large FMD epidemic within the livestock industry, and could provide insights into the rapid-transmission dynamics of the disease across long distances, despite a standstill of animal movements during the epidemic, given a single incursion of infection in any slaughterhouse in the country.

Adaptive Success Rate-based Sensor Relocation for IoT Applications

  • Kim, Moonseong;Lee, Woochan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.9
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    • pp.3120-3137
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    • 2021
  • Small-sized IoT wireless sensing devices can be deployed with small aircraft such as drones, and the deployment of mobile IoT devices can be relocated to suit data collection with efficient relocation algorithms. However, the terrain may not be able to predict its shape. Mobile IoT devices suitable for these terrains are hopping devices that can move with jumps. So far, most hopping sensor relocation studies have made the unrealistic assumption that all hopping devices know the overall state of the entire network and each device's current state. Recent work has proposed the most realistic distributed network environment-based relocation algorithms that do not require sharing all information simultaneously. However, since the shortest path-based algorithm performs communication and movement requests with terminals, it is not suitable for an area where the distribution of obstacles is uneven. The proposed scheme applies a simple Monte Carlo method based on relay nodes selection random variables that reflect the obstacle distribution's characteristics to choose the best relay node as reinforcement learning, not specific relay nodes. Using the relay node selection random variable could significantly reduce the generation of additional messages that occur to select the shortest path. This paper's additional contribution is that the world's first distributed environment-based relocation protocol is proposed reflecting real-world physical devices' characteristics through the OMNeT++ simulator. We also reconstruct the three days-long disaster environment, and performance evaluation has been performed by applying the proposed protocol to the simulated real-world environment.

World Representation Using Complex Network for Reinforcement Learning (복잡계 네트워크를 이용한 강화 학습에서의 환경 표현)

  • 이승준;장병탁
    • Proceedings of the Korean Information Science Society Conference
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    • 2004.04b
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    • pp.622-624
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    • 2004
  • 강화 학습(Reinforcement Learning)을 실제 문제에 적용하는 데 있어 가장 큰 문제는 차원성의 저주(Curse of dimensionality)였다 문제가 커짐에 따라 목적을 이루기 위해서 더 많은 단계의 판단이 필요하고 이에 따라 문제의 해결이 지수적으로 어려워지게 된다. 이를 해결하기 위해 문제를 여러 단계로 나누어 단계별로 학습하는 계층적 강화 학습(Hierarchical Reinforcement Learning)이 제시된 바 있다 하지만 대부분의 계층적 강화 학습 방법들은 사전에 문제의 구조를 아는 것을 전제로 하며 큰 사이즈의 문제를 간단히 표현할 방법을 제시하지 않는다. 따라서 이들 방법들도 실제적인 문제에 바로 적용하기에는 적합하지 않다. 최근 이루어진 복잡계 네트워크(Complex Network)에 대한 연구에 착안하여 본 논문은 자기조직화하는 생장 네트워크(Self organizing growing network)를 기반으로 한 간단한 환경 표현 모델을 사용하는 강화 학습 알고리즘을 제안한다 네트웍은 복잡계 네트웍이 갖는 성질들을 유지하도록 자기 조직화되고, 노드들 간의 거리는 작은 세상 성질(Small World Property)에 따라 전체 네트웍의 큰 사이즈에 비해 짧게 유지된다. 즉 판단해야할 단계의 수가 적게 유지되기 때문에 이 방법으로 차원성의 저주를 피할 수 있다.

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