• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.2
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• pp.151-156
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• 2005

This paper proposes a Distributed Autonomous Robotic System(DARS) based on an Artificial Immune System(AIS) 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 given environment. These actions are composed of two types: aggregation and dispersion. AIS decides one among 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 one. The proposed system will be more adaptive than the existing system at the viewpoint that the robots learn and adapt the changing of tasks.

• Journal of Korean Association for Spatial Structures
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• v.9 no.1
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• pp.53-60
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• 2009

The purpose of this study is to explore the methodology of structural planning and detail, maintaining a close connection between architect and structural engineer. Actually it is difficult to solve a detail in a special structure, without investigation of structural behavior. In such a detail, it is hard to estimate the accurate flow of force, no more than a formative presentation. I will purpose to solve the processing of desirable detail, as a point of engineer's view, under the cooperative relationship between architect and structural engineer.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.3030-3032
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• 1999

This Paper proposes a fuzzy algorithm for cooperative behaviors of multiple autonomous mobile robots. Each robot makes decision of his behavior based on the information obtained by infrared sensors to measure the position and velocities of other robots. The effectiveness of the proposed algorithm is shown by some computer simulation where a group of mobile robots encircles with equi-interval.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.871-872
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• 2014

In this paper, I propose the method of cooperative work of swarm robot for escaping maze. The robots can communicate with each other using Zigbee, but the central control system send commands to robots because of low processing power of robots. Robots navigate the blinded maze and send information such as movement to the central control system for building map. The central control system analysis the received data and find path to escape from maze.

• Food Science of Animal Resources
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• v.38 no.5
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• pp.995-1007
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• 2018

Changes in the physicochemical properties of ready-to-feed liquid infant formula (LIF) stored at different temperatures (10, 20, 30, and $40^{\circ}C$) for 6 mon, focusing on 5-hydroxymethylfurfural (HMF) content, color, pH, fat globule size distribution, and rheological properties were determined. The HMF content increased with storage time, and LIF stored at $40^{\circ}C$ had a higher HMF content than that of LIF stored at $10^{\circ}C$. The lightness ($L^*$) decreased while redness ($a^*$) and yellowness ($b^*$) increased with increasing HMF content. The fat globule size and pH of LIF stored at $10^{\circ}C$ did not change. However, in the case of LIF stored at $30^{\circ}C$ and $40^{\circ}C$, the fat globule size increased and the pH decreased during storage for 6 mon. LIF stored at $40^{\circ}C$ had a higher apparent viscosity (${\eta}_{a,10}$) than that of LIF stored at $10^{\circ}C$, and the shear-thinning behavior of LIF stored at higher temperature was stronger than that of LIF stored at low temperature. The physicochemical changes of LIF during storage were accelerated by Maillard reaction (MR) at higher storage temperatures. Therefore, even if LIF is aseptically manufactured, we recommend that sterilized LIF should be stored at low temperature in order to minimize quality changes during storage.

• Korean Journal of Cognitive Science
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• v.11 no.1
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• pp.67-80
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• 2000

Distributed cooperative information system is the one that has various knowledge sources as well as problem solving capabilities to get information in a distributed and heterogeneous data environment. In a distributed cooperative information system. a control mechanism to facilitate the available information is very important. and usually the role of the control mechanism determines the behavior of the total system In this research. we proposed a model of the distributed cooperative information system which is based on the multi-agent paradigm. We also implemented a test system to show l its feasibility. The proposed system makes the knowledge sources into agents and a special agent called 'facilitator' controls the cooperation between the knowledge agents The facilitator uses the knowledge granularity level to determine the sequence of the activation of the agents. In other words. the knowledge source with simple but fast processing mechanism activates first while more sophisticated but slow knowledge sources are activated late. In an environment in which we have several knowledge sources for the same topic. the proposed system will simulate the focusing mechanism of human cognitive process.

• Journal of Korea Game Society
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• v.15 no.5
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• pp.89-98
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• 2015

The artificial intelligence (AI) of Non-Player Companions (NPC), especially opponents, is a key element to adjust the level of games in game design. Smart opponents can make games more challenging as well as allow players for diverse experiences, even in the same game environment. Since game users interact with more than one opponent in most of today's games, collaboration control of opponent characters becomes more important than ever before. In this paper, we introduce a cooperative strategy based on the A* algorithm for enemies' AI in the Pac-Man game. A survey from 17 human testers shows that the levels with our collaborative opponents are more difficult but interesting than those with either the original Pac-Man's personalities or the non-cooperative greedy opponents.

• Hwankyungkyoyuk
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• v.13 no.2
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• pp.38-50
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• 2000

We are evidently Home Economicus, egoistic rational utility maximiger, and all the capitalism economic situation make us adapt to such life, and recognize that it is rational to act like that. This can be demonstrated in Prisoner′s Dilemma(PD) which always select the non-cooperative choice for free rider in rational selection process of public goods. This paper notice the "what is problem\ulcorner"The problem is not in free rider itself but in free rider egoism. The practical behavior of free rider egoism can be explained by way of Prisoner′s Dilemma. In PD situation, the prisoner makes a rational choice, non-cooperative alternative, but he doesn′arrive at preto-optimality. It is dilemma. Why can′t he arrive \ulcorner Because he is isolated from other prisoner. So we call it prisoner′s dilemma. The PD situation can be compared with our real economic life, which, we think, have kept by rational choice of the public goods. We actually have made our life as an individual one although we organized communities of capitalism. Of course, we know each others as members of same society, but each individual being can′t secure the belief, which has composed basis of community. So, it is very similar and common between PD situation and our real economic life in the production of public goods. We conclude that this non-cooperative process of PD situation can be utilized as instrument of EE. So this non-cooperative process can show us the effectiveness of EE as follows. \circled1 Game situation life PD can be used as good instrument for explaining the rational selection dilemma(error) to Homo-Economicus, the rational agent, with the optimal and rational language. \circled2 We can show that the selection result is dilemma, not arrive pareto - optimality. \circled3 The dilemma can be resolved with accomplishing the good communal life based on the belief, not on the isolation.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.8
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• pp.56-64
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• 1997

In distributed autonomous robotic systems, each robot must behaves by itself according to the its states and environements, and if necessary, must cooperates with other orbots in order to carray 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 reinforement learning having delayed reward ability and distributed genectic algorithms is proposed for behavior learning and evolution of collective autonomous mobile robots. Reinforement 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 perfodrmance 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.

• Journal of the Ergonomics Society of Korea
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• v.6 no.1
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• pp.9-24
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• 1987

The design and philosophy are presented for an intelligent aid for a hyman operator who must diagnose a novel fault in a physical system. A novel fault is defined as one that the operator has not experienced in either real system operation or training. When the operator must diagnose a novel fault, deep reasoning about the behavior of the system components is required. To aid the human operator in this situation, four aiding approaches which provide useful information are proposed. The aiding information is generated by a qualitative, component-level model of the physical system. Both the aid and the human are able to reason causally about the system in a cooperative search for a diagnosis. The aiding features were designed to help the hyman's use of his/her mental model in predicting the normal system behavior, integrating the observations into the actual system behavior, or finding discrepancies between the two. The aid can also have direct access to the operator's hypotheses and run a hypothetical system model. The different aiding approaches will be evaluated by a series of experiments.