• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권11호
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• pp.5322-5342
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• 2016

In vehicle-to-vehicle (V2V) networks, where selfishness degrades node activity, countermeasures for collaboration enforcement must be provided to enable application of a sage and efficient network environment. Because vehicular networks feature both high mobility and various topologies, selfish behavior judgment and establishment of a stable routing protocol become intensely challenging. In this paper, a two-phase-based generous cooperative routing protocol (called GEC) is presented for V2V networks to provide resistance to selfishness. To detect selfish behaving vehicles, a packet forwarding watchdog and an average connection rate based on the multipath weight method are used, where evidence is gathered from different watchdogs. Then, multihop relay decisions are made using a generous cooperative algorithm based on game theory. Finally, through buffering of the multiple end-to-end paths and judicious choice of optimal cooperative routes, route maintenance phase is capable of dealing with congestion and rapidly exchanging traffic. Specifically, it is proved that the GEC is theoretically subgame perfect. Simulation results show that for V2V networks with inherently selfish nodes, the proposed method isolates uncooperative vehicles and is capable of accommodating both the mobility and congestion circumstances by facilitating information dissemination and reducing end-to-end delay.

• 한국국방경영분석학회지
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• 제27권1호
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• pp.114-127
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• 2001

To support cooperative work in various scenes by computer systems, functions of sharing personalization, observation and control are needed. Especially, in advanced cooperative work, people have various position so that sometimes one person needs to restrict behavior of another. In this paper, we describe representation of access restriction of hypermedia system, which is framework of CSCW(Computer-Supported Cooperative Works) system we developed and propose a way to go on working cooperatively with people, restricting others.

• 전자공학회논문지S
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• 제35S권3호
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• pp.102-109
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• 1998

In this paper, we propose a method of cooperative control based on immune system in distributed autonomous robotic system(DARS). Immune system is living body's self-protection and self-maintenance system. Thus these features can be applied to decision making of optimal swarm behavior in dynamically changing environment.For the purpose of applying immune system to DARS, a robot is regarded as a B lymphocyte(B cell), each environmental condition as an antigen, and a behavior strategy as an antibody respectively. The executing process of proposed method is as follows. When the environmental codintion changes, a robot select an appropriate beharior stategy. And its behavior stategy is stimulated and suppressed by other robot using communiation. Finally much stimulated strategy is adopted as a swarm behavior strategy. This control scheme is based on clonal selection and idotopic network hypothesis. And it is used for decision making of optimal swarm stragegy.

• 한국지능시스템학회논문지
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• 제16권1호
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• pp.72-78
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• 2006

군집 로봇시스템에서 협조 행동을 위기 위해서는 로봇의 센싱과 통신 기능은 필수적이다. 일반적으로 대역적 통신 시스템에서는 로봇의 대수가 증가하면 통신 자원의 제한과 정보의 범람이 발생한다. 따라서 이 경우 지역적 통신방법이 유리하다. 따라서 본 논문에서는 지역적 통신에 의한 정보의 전파 해석을 통하여 최적의 통신 반경을 결정하는 방법을 제안하고, 이를 이용하여 인공면역계에 기반한 군집 로봇시스템의 협조 전략과 군 행동 알고리즘을 제안한다.

• 한국지능시스템학회논문지
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• 제16권2호
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• pp.131-137
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• 2006

군집 로봇시스템에서 개개의 로봇은 스스로 주위의 환경과 자신의 상태를 스스로 판단하여 행동하고, 필요에 따라서는 다른 로봇과 협조를 통하여 어떤 주어진 일을 수행할 수 있어야 한다. 따라서 개개의 로봇은 동적으로 변화하는 환경에 잘 적응할 수 있는 학습과 진화능력을 갖는 것이 필수적이다. 이를 위하여 본 논문에서는 지연된 보상능력이 있는 강화학습과 분산유전알고리즘을 이용한 새로운 자율이동로봇의 행동학습 및 진화방법을 제안한다. 지연 보상능력이 있는 강화학습은 로봇이 취한 행동에 대하여 즉각적인 보상을 가할 수 없는 경우에도 학습이 가능한 방법이다. 또한 개개의 로봇이 통신을 통하여 염색체를 교환하는 분산유전알고리즘은 각기 다른 환경에서 학습한 우수한 염색체로부터 자신의 능력을 향상시킨다. 특히 본 논문에서는 진화의 성능을 향상시키기 위하여 강화학습의 특성을 이용한 선택 교배방법을 채택하였다. 제안된 방법은 협조탐색 문제에 적용하여 컴퓨터 시뮬레이션을 통하여 그 유효성을 검증한다.

• 제어로봇시스템학회논문지
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• 제6권12호
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• pp.1079-1085
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• 2000

In this paper, we propose a method of cooperative control (T-cell modeling) and selection of group behavior strategy (B-cell modeling) based on immune system in distributed autonomous robotic system (DARS). An immune system is the living bodys self-protection and self-maintenance system. these features can be applied to decision making of the optimal swarm behavior in a dynamically changing environment. For applying immune system to DARS, a robot is regarded as a B-cell, each environmental condition as an antigen, a behavior strategy as an antibody, and control parameter as a T-cell, respectively. When the environmental condition (antigen) changes, a robot selects an appropriate behavior strategy (antibody). And its behavior strategy is stimulated and suppressed by other robots using communication (immune network). Finally, much stimulated strategy is adopted as a swarm behavior strategy. This control scheme is based on clonal selection and immune network hypothesis, and it is used for decision making of the optimal swarm strategy. Adaptation ability of the robot is enhanced by adding T-cell model as a control parameter in dynamic environments.

• Journal of Communications and Networks
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• 제13권3호
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• pp.266-276
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• 2011

In wireless networks, it is well-known that intermediate nodes can be used as cooperative relays to reduce the transmission energy required to reliably deliver a message to an intended destination. When the network is under a central authority, energy allocations and cooperative pairings can be assigned to optimize the overall energy efficiency of the network. In networks with autonomous selfish nodes, however, nodes may not be willing to expend energy to relay messages for others. This problem has been previously addressed through the development of extrinsic incentive mechanisms, e.g., virtual currency, or the insertion of altruistic nodes in the network to enforce cooperative behavior. This paper considers the problem of how selfish nodes can decide on an efficient energy allocation and endogenously form cooperative partnerships in wireless networks without extrinsic incentive mechanisms or altruistic nodes. Using tools from both cooperative and non-cooperative game theory, the three main contributions of this paper are (i) the development of Pareto-efficient cooperative energy allocations that can be agreed upon by selfish nodes, based on axiomatic bargaining techniques, (ii) the development of necessary and sufficient conditions under which "natural" cooperation is possible in systems with fading and non-fading channels without extrinsic incentive mechanisms or altruistic nodes, and (iii) the development of techniques to endogenously form cooperative partnerships without central control. Numerical results with orthogonal amplify-and-forward cooperation are also provided to quantify the energy efficiency of a wireless network with sources selfishly allocating transmission/relaying energy and endogenously forming cooperative partnerships with respect to a network with centrally optimized energy allocations and pairing assignments.

• Journal of Ubiquitous Convergence Technology
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• 제1권1호
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• pp.53-59
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• 2007

This paper proposes a new group mobility model for wireless communication. The mobility model considers the psychological and sociological behavior of each node and the perception of other nodes for describing interactions among a set of nodes. The model assumes no permanent membership of a group, capable of capturing natural behaviors as fork and join. It emulates a cooperative movement pattern observed in mobile ad hoc networks of military operation and campus, in which a set of mobile stations accomplish a cooperative motion affected by the individual behavior as well as a group behavior. The model also employs a physic model to avoid a sudden stopping and a sharping turning.

• 한국지능시스템학회논문지
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• 제17권5호
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• pp.591-597
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• 2007

군집 로봇시스템에서 개개의 로봇은 스스로 주위의 환경과 자신의 상태를 스스로 판단하여 행동하고, 필요에 따라서는 다른 로봇과 협조를 통하여 어떤 주어진 일을 수행할 수 있어야 한다. 따라서 개개의 로봇은 동적으로 변화하는 환경에 잘 적응할 수 있는 학습과 진화능력을 갖는 것이 필수적이다 이를 위하여 본 논문에서는 새로운 Polygon 기반의 Q-learning 알고리즘과 분산유전알고리즘을 이용한 새로운 자율이동로봇의 행동학습 및 진화방법을 제안한다. 또한 개개의 로봇이 통신을 통하여 염색체를 교환하는 분산유전알고리즘은 각기 다른 환경에서 학습한 우수한 염색체로부터 자신의 능력을 향상시킨다. 특히 본 논문에서는 진화의 성능을 향상시키기 위하여 강화학습의 특성을 이용한 선택 교배방법을 채택하였다. 제안된 방법은 협조탐색 문제에 적용하여 컴퓨터 모의실험을 통하여 그 유효성을 검증한다.

• 한국수학교육학회지시리즈A:수학교육
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• 제53권3호
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• pp.399-412
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• 2014

The purpose of this article is to suggest using cooperative microteaching in pre-service mathematics teachers education based on their perceptions of it after actual application case. The background of this study is that cooperative learning came into the highlight as a good method to cultivate teachers' competencies for creativity and character education as well as students' creativity and character in the mathematics classroom. 20 pre-service mathematics teachers participated in their cooperative microteaching and 16 of them responded to the survey. The collected data showed that the merits of cooperative microteaching are to ease the burden of preparing for class, to discuss how to teach mathematics, to debate what lesson is better, to receive valuable feedback form their peer, and so on. Also, it provided them with the chance for self-improvement in that they kept to make up for the week points in their teaching behavior. Meanwhile, they wanted longer time to experience their teaching and their own lesson.