• Title/Summary/Keyword: Cooperative search

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Using Potential Field for Modeling of the Work-environment and Task-sharing on the Multi-agent Cooperative Work

  • Makino, Tsutomu;Naruse, Keitarou;Yokoi, Hiroshi;Kakazu, Yikinori
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2001.01a
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    • pp.37-44
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    • 2001
  • This paper describes the modeling of work environment for the extraction of abstract operation rules for cooperative work with multiple agent. We propose the modeling method using a potential field. In the method, it is applied to a box pushing problem, which is to move a box from a start to a goal b multiple agent. The agents follow the potential value when they move and work in the work environment. The work environment is represented as the grid space. The potential field is generated by Genetic Algorithm(GA) for each agent. GA explores the positions of a potential peak value in the grid space, and then the potential value stretching in the grid space is spread by a potential diffusion function in each grid. However it is difficult to explore suitable setting using hand coding of the position of peak potential value. Thus, we use an evlolutionary computation way because it is possible to explore the large search space. So we make experiments the environment modeling using the proposed method and verify the performance of the exploration by GA. And we classify some types from acquired the environment model and extract the abstract operation rule, As results, we find out some types of the environment models and operation rules by the observation, and the performance of GA exploration is almost same as the hand coding set because these are nearly same performance on the evaluation of the consumption of agent's energy and the work step from point to the goal point.

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Behavior Learning and Evolution of Individual Robot for Cooperative Behavior of Swarm Robot System (군집 로봇의 협조 행동을 위한 로봇 개체의 행동학습과 진화)

  • Sim, Kwee-Bo;Lee, Dong-Wook
    • Journal of the Korean Institute of Intelligent Systems
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    • v.16 no.2
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    • pp.131-137
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    • 2006
  • In swarm robot systems, each robot must behaves by itself according to the its states and environments, and if necessary, must cooperates with other robots in order to carry out a given task. Therefore it is essential that each robot has both learning and evolution ability to adapt the dynamic environments. In this paper, the new learning and evolution method based on reinforcement learning having delayed reward ability and distributed genetic algorithms is proposed for behavior learning and evolution of collective autonomous mobile robots. Reinforcement learning having delayed reward is still useful even though when there is no immediate reward. And by distributed genetic algorithm exchanging the chromosome acquired under different environments by communication each robot can improve its behavior ability. Specially, in order to improve the performance of evolution, selective crossover using the characteristic of reinforcement learning is adopted in this paper. we verify the effectiveness of the proposed method by applying it to cooperative search problem.

An Efficient Neighbor Discovery Method for Cooperative Video Surveillance Services in Internet of Vehicles (차량 인터넷에서 협업 비디오 감시 서비스를 위한 효율적인 이웃 발견 방법)

  • Park, Taekeun;Lee, Suk-Kyoon
    • Journal of Information Technology Services
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    • v.15 no.4
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    • pp.97-109
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    • 2016
  • The rapid deployment of millions of mobile sensors and smart devices has resulted in high demand for opportunistic encounter-based networking. For the cooperative video surveillance of dashboard cameras in nearby vehicles, a fast and energy-efficient asynchronous neighbor discovery protocol is indispensable because a dashboard camera is an energy-hungry device after the vehicle's engine has turned off. In the existing asynchronous neighbor discovery protocols, all nodes always try to discover all neighbors. However, a dashboard camera needs to discover nearby dashboard cameras when an event is detected. In this paper, we propose a fast and energy-efficient asynchronous neighbor discovery protocol, which enables nodes : 1) to have different roles in neighbor discovery, 2) to discover neighbors within a search range, and 3) to report promptly the exact discovery result. The proposed protocol has two modes: periodic wake-up mode and active discovery mode. A node begins with the periodic wake-up mode to be discovered by other nodes, switches to the active discovery mode on receiving a neighbor discovery request, and returns to the periodic wake-up mode when the active discovery mode finishes. In the periodic wake-up mode, a node wakes up at multiples of number ${\alpha}$, where ${\alpha}$ is determined by the node's remaining battery power. In the active discovery mode, a node wakes up for consecutive ${\gamma}$ slots. Then, the node operating in the active discovery mode can discover all neighbors waking up at multiples of ${\beta}$ for ${\beta}{\leq}{\gamma}$ within ${\gamma}$ time slots. Since the proposed protocol assigns one half of the duty cycle to each mode, it consumes equal to or less energy than the existing protocols. A performance comparison shows that the proposed protocol outperforms the existing protocols in terms of discovery latency and energy consumption, where the frequency of neighbor discovery requests by car accidents is not constantly high.

Reinforcement Learning Based Evolution and Learning Algorithm for Cooperative Behavior of Swarm Robot System (군집 로봇의 협조 행동을 위한 강화 학습 기반의 진화 및 학습 알고리즘)

  • Seo, Sang-Wook;Kim, Ho-Duck;Sim, Kwee-Bo
    • Journal of the Korean Institute of Intelligent Systems
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    • v.17 no.5
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    • pp.591-597
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    • 2007
  • In swarm robot systems, each robot must behaves by itself according to the its states and environments, and if necessary, must cooperates with other robots in order to carry out a given task. Therefore it is essential that each robot has both learning and evolution ability to adapt the dynamic environments. In this paper, the new polygon based Q-learning algorithm and distributed genetic algorithms are proposed for behavior learning and evolution of collective autonomous mobile robots. And by distributed genetic algorithm exchanging the chromosome acquired under different environments by communication each robot can improve its behavior ability Specially, in order to improve the performance of evolution, selective crossover using the characteristic of reinforcement learning is adopted in this paper. we verify the effectiveness of the proposed method by applying it to cooperative search problem.

Proposal of East-West Integrative Medicine Manual for Mild Cognitive Impairment in a Korean Medicine Hospital (일개 한의의료기관 내 경도인지장애의 의한협진 매뉴얼 제안)

  • Kim, Bomin;Jo, Hee-Guen;Kang, Hyung-Won;Choi, Sung-Youl;Song, Min-Yeong;Sul, Jae-Uk;Leem, Jungtae;Lee, Ga-Won;Son, Sung-Eun
    • Journal of Oriental Neuropsychiatry
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    • v.29 no.4
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    • pp.239-253
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    • 2018
  • Objectives: This is one of the manuals of East-West integrative medicine, which was created by the Committee on integrative medicine of Chung-Yeon Korean Medicine Hospital. To support clinical decision making and communication in the East-West cooperative treatment of mild cognitive impairment. Methods: Drafting was based on literature review from the MEDLINE, EMBASE, OASIS, and CNKI databases using search terms such as 'mild cognitive impairment', 'mild neurocognitive disorder', 'acupuncture', 'herbal medicine' and 'traditional Chinese medicine'. An amendment reflecting the goal of consultation and detailed treatment contents was made by reviewing the draft and holding discussion with the rehabilitation specialist of western medicine. The committee then agreed to adopt the manual through the process of review and feedback in addition to face-to-face discussions. Results: This manual contains the diagnosis of mild cognitive impairment, the goal of consultation, and the cooperative treatment contents of the East-West medicine for mild cognitive impairment. Conclusions: This manual provides significant information about the decision making process and contents of treatment in one medical institution for East-West cooperative treatment of mild cognitive impairment.

The Impact of External Search Strategy on Radical Innovation Performance (외부지식 탐색 전략이 급진적 혁신성과에 미치는 영향)

  • Ahn, He Soung;Kim, Juhee
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.13 no.2
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    • pp.101-113
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    • 2018
  • This paper investigates the relationship between external search strategy and radical innovation performance. As the discrepancies that can exist among the varying sources of external knowledge is overlooked, the existing literature on the effect of external search strategy on radical innovation performance remains inconclusive. This study aims to reconcile such mixed findings by recognizing that external knowledge can be distinctive depending on the environment in which its source is embedded in; specifically, this paper examines the relationship between external search strategy and radical innovation performance by distinguishing external search from 'market' and 'non-market' relationships. We test our hypotheses with a sample of 431 firms from the manufacturing industries from the 2010 STEPI survey. Our empirical findings suggest that external search strategy from market relationships positively influences radical innovation performance, while the influence of external search strategy from non-market relationships is found to be not significant. Our research suggests that in order to improve radical innovation performance, firms must be able to maintain a cooperative relationship with other actors connected with market relationships and to effectively exploit the market knowledge obtained from these actors.

Detection of Faces Located at a Long Range with Low-resolution Input Images for Mobile Robots (모바일 로봇을 위한 저해상도 영상에서의 원거리 얼굴 검출)

  • Kim, Do-Hyung;Yun, Woo-Han;Cho, Young-Jo;Lee, Jae-Jeon
    • The Journal of Korea Robotics Society
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    • v.4 no.4
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    • pp.257-264
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    • 2009
  • This paper proposes a novel face detection method that finds tiny faces located at a long range even with low-resolution input images captured by a mobile robot. The proposed approach can locate extremely small-sized face regions of $12{\times}12$ pixels. We solve a tiny face detection problem by organizing a system that consists of multiple detectors including a mean-shift color tracker, short- and long-rage face detectors, and an omega shape detector. The proposed method adopts the long-range face detector that is well trained enough to detect tiny faces at a long range, and limiting its operation to only within a search region that is automatically determined by the mean-shift color tracker and the omega shape detector. By focusing on limiting the face search region as much as possible, the proposed method can accurately detect tiny faces at a long distance even with a low-resolution image, and decrease false positives sharply. According to the experimental results on realistic databases, the performance of the proposed approach is at a sufficiently practical level for various robot applications such as face recognition of non-cooperative users, human-following, and gesture recognition for long-range interaction.

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A Study on Developing and Applying Access Point Control System Using SRU Protocol (SRU 프로토콜을 이용한 접근점제어 시스템의 구축과 활용에 관한 연구)

  • Lee, Ji-Won;Kim, Tae-Soo
    • Journal of the Korean Society for information Management
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    • v.22 no.1 s.55
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    • pp.229-248
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    • 2005
  • This study proposes a national cooperative model of access point control, that enables local systems to utilize national access point control record, without creating their own authority records. In order to applying this model, a client/server system is developed using SRU (Search and Retrieve URL Service) protocol. The suggested access point control system will be a cost-effective and time-saving model for the local system, and will be more flexible and extensible with concept of access point control, XML record format and SRU protocol.

Adaptive Distributed Autonomous Robotic System based on Artificial Immune Network and Classifier System

  • Hwang, Chul-Min;Sim, Kwee-Bo
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.1286-1290
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    • 2004
  • This paper proposes a Distributed Autonomous Robotic System (DARS) based on an Artificial Immune Network (AIN) and a Classifier System (CS). The behaviors of robots in the system are divided into global behaviors and local behaviors. The global behaviors are actions to search tasks in environment. These actions are composed of two types: aggregation and dispersion. AIN decides one between these two actions, which robot should select and act on in the global. The local behaviors are actions to execute searched tasks. The robots learn the cooperative actions in these behaviors by the CS in the local. The relation between global and local increases the performance of system. Also, the proposed system is more adaptive than the existing system at the viewpoint that the robots learn and adapt the changing of tasks.

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Analysis on the definition and typology of library networks (도서관 네트워크의 정의의 분석과 유형별 특성)

  • 박준식
    • Journal of Korean Library and Information Science Society
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    • v.12
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    • pp.1-33
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    • 1985
  • This study has been aimed to analyze the following three points which are believed to be the most important in establishing efficient library networks. The writers have done the research into the literature and references concerning the networks of library, as they are considered crucial functions in cooperative administration between the libraries. The following are the findings from the survey: 1) The established networks in foreign countries have been compared with those of Korea, basing upon the data and present situations in both areas and the definition and agreed viewpoint of the networks are presented. 2) The relations between the existing Library system and Consortia were clarified in view of the current trend, thus showing the scope and integral aspects of them. 3) Finally, we have classified the types of network into four categories, such as search service network, customized service network, service center/network and state local networks, and made through analysis of the character, organization and management of each realm.

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