• 대한전기학회논문지:전력기술부문A
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• 제48권9호
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• pp.1154-1160
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• 1999

A rule based controller is constructed for multiple robots accomplishing a given task in unknown environments by using genetic programming. The example task is playing a simplified soccer game, and the controller for robots that governs emergent cooperative behavior is successfully found using the proposed procedure A neural network controller constructed using the rule based controller is shown to be applicable in a more complex environment.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 G
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• pp.2197-2199
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• 1998

Many multiagents cooperative problems, such as table transport problem, require several emergent behaviors and a proper coordination of these is essential for successful accompishment of the task. We study in this paper the genetic programming method, called fitness switching, to evolve cooperation strategies of robots in these kind of tasks and show simulation results to demonstrate its effectiveness.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.170-175
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• 1998

Transporting a large table using multiple robotic agents requires at least two group behaviors of homing and herding which are to bo coordinated in a proper sequence. Existing GP methods for multi-agent learning are not practical enough to find an optimal solution in this domain. To evolve this kind of complex cooperative behavior we use a novel method called fitness switching. This method maintains a pool of basis fitness functions each of which corresponds to a primitive group behavior. The basis functions are then progressively combined into more complex fitness functions to co-evolve more complex behavior. The performance of the presented method is compared with that of two conventional methods. Experimental results show that coevolutionary fitness switching provides an effective mechanism for evolving complex emergent behavior which may not be solved by simple genetic programming.

• International Journal of Control, Automation, and Systems
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• 제1권1호
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• pp.149-155
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• 2003

In this study, we introduce the main ideas on the control and strategy used by the robot soccer team of the Universidad de Buenos hires, UBA-Sot. The basis of our approach is to obtain a cooperative behavior, which emerges from homogeneous sets of individual behaviors. Except for the goalkeeper, the behavior set of each robot contains a small number of individual behaviors. Basically, the individual behaviors have the same core: to move from the initial to-ward the target coordinates. However, these individual behaviors differ because each one has a different precondition associated with it. Each precondition is the combination of a number of elementary ones. The aim of our approach is to answer the following questions: How can the robot compute the preconditions in time\ulcorner How are the control actions defined, which allow the robot to move from the initial toward the final coordinates\ulcorner The way we cope with these issues is, on the one hand, to use ball and robot predictors and, on the other hand, to use very fast planning. Our proposal is to use planning in such a way that the behavior obtained is closer to a reactive than a deliberative one. Simulations and experiments on real robots, based on this approach, have so far given encouraging results.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1998년도 제13차 학술회의논문집
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• pp.507-512
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• 1998

It is an interesting area in the field of artificial intelligence to and an analytic model of cooperative structure for multi-agent system accomplishing a given task. Usually it is difficult to design controllers for multi-agent systems without a comprehensive knowledge about the system. One of the way to overcome this limitation is to implement an evolutionary approach to design the controllers. This paper introduces the use of a genetic algorithm to discover a fuzzy logic controller with rules that govern emergent co-operative behavior: A modified genetic algorithm was applied to automating the discovery of a fuzzy logic controller jot multi-agents playing a pursuit game. Simulation results indicate that, given the complexity of the problem, an evolutionary approach to and the fuzzy logic controller seems to be promising.

• 한국건설관리학회논문집
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• 제14권6호
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• pp.49-60
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• 2013

건축물에 있어 피난 계획은 프로젝트 전반에 걸쳐 고려되어야 할 매우 중요한 요소 중 하나이다. 기존 다양한 연구 및 실제 재난 사례등을 통해 피난의 중요성은 지속적으로 강조되어 왔으며, 사전 대비를 위한 다양한 노력들이 수행되어 왔다. 또한, 실제와 유사한 대응 훈련 준비의 어려움을 극복하고자 시뮬레이션을 통한 해결책 마련이 새로운 대안으로 떠올랐다. 그러나 피난 계획의 경우 시설물 뿐만 아니라 재실자의 특성 또한 신중히 고려되어야 한다. 현실과 가까운 피난 계획의 수립을 위해 본 연구에서는 인간 행태를 고려한 피난 과정을 분석한다. 기존 사회과학 이론에 기초하고 시스템 다이내믹스 모델링을 이용하여, 피난 초기부터 탈출까지 다양한 재실자 그룹의 특성으로 인해 발생하는 요인들을 포함하며, 이에 따른 의사결정, 행동의 변화 등의 분석한다. 이러한 모델을 통해 그룹 형성 및 재실자 간 상호 작용 등 긴급 상황에서 발생하는 인간 행태가 전체 피난 행태 및 결과에 미치는 영향을 파악하며, 향후 피난 시뮬레이터의 모듈로써의 활용 및 시설물 안전 관리자의 피난 계획 수립 시 의사결정의 기초자료를 제공할 것이라 예상된다.