• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.275-276
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• 2006

An intelligent arm-wrestling system is recently developed in our laboratory that is comprised of an arm-force generation mechanism and a control system that detects the maximum arm-force of a user in the early stage of the match, generates a different game scenario each time, and executes force feedback control to implement the scenario. This paper presents the mathematical model of the force control system of the intelligent arm-wrestling system, and some improvements of it via experimental frequency responses using a control signal analyzer.

• Journal of Information Processing Systems
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• v.15 no.5
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• pp.1192-1200
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• 2019

Recently, artificial intelligence techniques have been widely used in the computer science field, such as the Internet of Things, big data, cloud computing, and mobile computing. In particular, resource management is of utmost importance for maintaining the quality of services, service-level agreements, and the availability of the system. In this paper, we review and analyze various ways to meet the requirements of cloud resource management based on artificial intelligence. We divide cloud resource management techniques based on artificial intelligence into three categories: fog computing systems, edge-cloud systems, and intelligent cloud computing systems. The aim of the paper is to propose an intelligent resource management scheme that manages mobile resources by monitoring devices' statuses and predicting their future stability based on one of the artificial intelligence techniques. We explore how our proposed resource management scheme can be extended to various cloud-based systems.

• Journal of Internet Computing and Services
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• v.16 no.6
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• pp.69-78
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• 2015

Recently, research on the multi-agent system is developed actively in the various fields, especially on the control of complex system and optimization. In this study, we develop a multi-agent system for NPC simulation in game environment. The purpose of the development is to support quick and precise decision by inferencing the situation of the dynamic discrete domain, and to support an optimization process of the agent system. Our approach employed Petri-net as a basic agent model to simplify structure of the system, and used fuzzy inference engine to support decision making in various situation. Our experimentation describes situation of the virtual battlefield between the NPCs, which are divided two groups, such as fuzzy rule based agent and automata based agent. We calculate the percentage of winning and survival rate from the several simulations, and the result describes that the fuzzy rule based agent showed better performance than the automata based agent.

• The KIPS Transactions:PartB
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• v.13B no.1 s.104
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• pp.15-20
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• 2006

This paper describes research on intelligent game character through performance enhancements of physics engine in computer games. The algorithm that recognizes the physics situation uses momentum back-propagation neural networks. Also, we present an experiment and its results, integration methods that display optimum performance based on the physics situation. In this experiment on integration methods, the Euler method was shown to produce the best results in terms of fps in a simulation environment with collision detection. Simulation with collision detection was shown similar fps for all three methods and the Runge-kutta method was shown the greatest accuracy. In the experiment on physics situation recognition, a physics situation recognition algorithm where the number of input layers (number of physical parameters) and output layers (destruction value for the master car) is fixed has shown the best performance when the number of hidden layers is 3 and the learning count number is 30,000. Since we tested with rigid bodies only, we are currently studying efficient physics situation recognition for soft body objects.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.3
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• pp.375-381
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• 2005

Usually genetic algorithms are used to design optimal system. However the performance of the algorithm is determined by the fitness function and the system environment. It is expected that a co-evolutionary algorithm, two populations are constantly interact and co-evolve, is one of the solution to overcome these problems. In this paper we propose three types of co-evolutionary algorithm to solve GA-Hard problem. The first model is a competitive co-evolutionary algorithm that solution and environment are competitively co-evolve. This model can prevent the solution from falling in local optima because the environment are also evolve according to the evolution of the solution. The second algorithm is schema co-evolutionary algorithm that has host population and parasite (schema) population. Schema population supply good schema to host population in this algorithm. The third is game model-based co-evolutionary algorithm that two populations are co-evolve through game. Each algorithm is applied to visual servoing, robot navigation, and multi-objective optimization problem to verify the effectiveness of the proposed algorithms.

• The KIPS Transactions:PartB
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• v.13B no.4 s.107
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• pp.449-456
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• 2006

This paper proposes intelligent characters for fighting action games to which energy points are applied for more realistic implementation than those of previous researches. The intelligent characters decide their actions in consideration of their energy level as well as a current action, the step of the action, the distance, and past actions of opponent characters that were used in existing intelligent ones. We used two types of energy, HP(Health Point) and MP(Mana Point) that were frequently employed in recent on-line games. We experimented with proposed intelligent characters to investigate whether the intelligent characters learn proper actions and cope with opponent characters in consideration of their energy levels. Experimental results showed that the intelligent characters reacted with the best actions to obtain high score if their energy is sufficient, Otherwise, they did the actions to(that?) recharge their energy. From this observation, we could conclude that the proposed intelligent characters worked well and did effective actions in consideration of the their energy.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.9
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• pp.2213-2218
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• 2013

Smart devices such as smart phone, smart TV, tablet, game consoles embrace all categories of Intelligent Communication Device, which enables intelligent applications to be developed, by up loading Context-aware Computing technology that recognizes and reacts nearby diverse phenomena and composing these information, as well as their basic functions. This paper, after saving pre-registered students' movement course and business places harmful to them into students safety network service system, by using location-based service and searching students' movement, considering the degree of breaking away from their regular course, the access to and their stay in crime-crone area, provides the comparative analysis of the system and suggests the ways for safe students guidance.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.3
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• pp.322-331
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• 2003

As the complexity of a 3D game is increased by various factors of the game scenario, it has a problem for controlling the interrelation of the game objects. Therefore, a game system has a necessity of the coordination of the responses of the game objects. Also, it is necessary to control the behaviors of animations of the game objects in terms of the game scenario. To produce realistic game simulations, a system has to include a structure for designing the interactions among the game objects. This paper presents a method that designs the dynamic control mechanism for the interaction of the game objects in the game scenario. For the method, we suggest a game agent system as a framework that is based on intelligent agents who can make decisions using specific rules. Game agent systems are used in order to manage environment data, to simulate the game objects, to control interactions among game objects, and to support visual authoring interface that ran define a various interrelations of the game objects. These techniques can process the autonomy level of the game objects and the associated collision avoidance method, etc. Also, it is possible to make the coherent decision-making ability of the game objects about a change of the scene. In this paper, the rule-based behavior control was designed to guide the simulation of the game objects. The rules are pre-defined by the user using visual interface for designing their interaction. The Agent State Decision Network, which is composed of the visual elements, is able to pass the information and infers the current state of the game objects. All of such methods can monitor and check a variation of motion state between game objects in real time. Finally, we present a validation of the control method together with a simple case-study example. In this paper, we design and implement the supervised classification systems for high resolution satellite images. The systems support various interfaces and statistical data of training samples so that we can select the most effective training data. In addition, the efficient extension of new classification algorithms and satellite image formats are applied easily through the modularized systems. The classifiers are considered the characteristics of spectral bands from the selected training data. They provide various supervised classification algorithms which include Parallelepiped, Minimum distance, Mahalanobis distance, Maximum likelihood and Fuzzy theory. We used IKONOS images for the input and verified the systems for the classification of high resolution satellite images.

• Journal of the Korea Computer Industry Society
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• v.7 no.3
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• pp.163-170
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• 2006

This paper proposes intelligent characters for fighting action games to which energy concepts are applied for more realistic implementation than those of previous researches. The intelligent characters decide their actions in consideration of their energy level as well as a current action, the step of the action, the distance, and past actions of opponent characters that were used in existing intelligent ones. We used two types of energy, HP(Health Point) and MP(Mana Point), that were frequently employed in recent on-line games. We experimented with proposed intelligent characters to investigate whether the intelligent characters loam proper actions and cope with opponent characters in consideration of their energy levels. Experimental results showed that the intelligent characters reacted to the best actions to obtain high score if their energy is sufficient, otherwise they did the actions to recharge their energy. From this observation, we could conclude that the proposed intelligent characters worked well and did effective actions in consideration to the their energy.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.18 no.4 s.119
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• pp.448-454
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• 2007

In this paper, the game theory based power control for CDMA system is studied, which has attained intensive interest as a core artificial intelligent technology fur cognitive Radio and its efficiency is evaluated using performance metrics such as system throughput and fairness. Utility Function for joint user centric and network centric power control is defined and simulation results show that game theory based power control is far better than closed loop power control. The contribution of this raper is to formalize the game theory based power control toward the cognitive radio that recognizes and adapts to the radio communication environments.