• Title/Summary/Keyword: Game Navigation Control

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Semantic Virtual Environment Generation and Navigation Control for 3D Games (3차원 게임을 위한 시맨틱 가상환경 생성과 네비게이션 제어)

  • Jang, Hyun-Duk;Lee, Jae-Moon;Lee, Myeong-Won
    • The KIPS Transactions:PartA
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    • v.14A no.4
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    • pp.209-214
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    • 2007
  • In conventional game systems, virtual environments usually have just the role of a background without the direct relationships for game characters. nev do not consider the semantics about virtual environments. In this paper, we develop a game navigation system that provides semantic information about virtual environments including geographical, historical or my other location-dependent information. Then, the game character obtains the geographical location and its related information when it navigates through a virtual environment. It can be an implementation method for a semantic virtual environment because it can have the environment maintain its semantics depending on the specific location. In addition, we describe a method that can control a character's motion in the semantic virtual environment interactively, and that can input specific information according to the location of the character.

Power Control Algorithm with Finite Strategies: Game Theoretic Approach (게임이론을 이용한 유한 전략 집합을 갖는 전력제어 알고리즘)

  • Kim, Ju-Hyup;Jang, Yeon-Sik;Lee, Deok-Joo;Hong, Een-Kee
    • Journal of Advanced Navigation Technology
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    • v.13 no.1
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    • pp.87-96
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    • 2009
  • The purpose of this paper is to analyze the power control problem in wireless communications with game theoretic approach. The major contribution of the present paper is that we formulated the problem as a game with a finite number of strategies while most of the previous game theoretic power control literatures modeled with continuous game in which there are infinite number of strategies. It should be noted that the closed-loop power control would be performed in a discrete manner, power up or down from the present level of power with fixed power control step size. We model the current closed-loop power control scheme with the famous Prisoner's dilemma model and show that the power-up strategy is Nash equilibrium. That is, every mobile tries to increase their power and approach to their maximal power. Thus, the outcome of current power control (Nash equilibrium) is inefficient. In order to attain efficient power control for the environment where ICI(Inter-Cell Interference is severe, we developed a new payoff function in which the penalty mechanism is introduced and derived conditions under which power-down becomes Nash equilibrium strategy for all players. Furthermore we examined the trajectory of equilibrium power when the power control game will be played repeatedly.

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Performance Analysis of Pursuit-Evasion Game-Based Guidance Laws

  • Kim, Young-Sam;Kim, Tae-Hun;Tahk, Min-Jea
    • International Journal of Aeronautical and Space Sciences
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    • v.11 no.2
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    • pp.110-117
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    • 2010
  • We propose guidance laws based on a pursuit-evasion game. The game solutions are obtained from a pursuit-evasion game solver developed by the authors. We introduce a direct method to solve planar pursuit-evasion games with control variable constraints in which the game solution is sought by iteration of the update and correction steps. The initial value of the game solution is used for guidance of the evader and the pursuer, and then the pursuit-evasion game is solved again at the next time step. In this respect, the proposed guidance laws are similar to the approach of model predictive control. The proposed guidance method is compared to proportional navigation guidance for a pursuit-evasion scenario in which the evader always tries to maximize the capture time. The capture sets of the two guidance methods are demonstrated.

Performance Analysis of Pursuit- Evasion Game Based Guidance Laws (추적-회피 게임 기반 유도법칙의 성능 분석)

  • Kim, Young-Sam;Tahk, Min-Jea;Ryu, Hyeok
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.36 no.8
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    • pp.747-752
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    • 2008
  • We propose a guidance law based on pursuit-evasion game solutions, and analyze its performance. The game solutions are obtained from the pursuit-evasion game solver developed by Tahk. The initial value of the game solution is used for guidance, and then the pursuit-evasion game is solved again at the next time step. In this respect, the proposed guidance laws are similar to the approach of model predictive control. The proposed guidance method is compared with proportional navigation guidance for a pursuit-evasion scenario, in which the evader always tries to maximize the capture time. According to the comparison, it has larger a capture set than ones of proportional navigation guidance law.

Game Algorithm for Power Control in Cognitive Radio Networks (전파 인지 네트워크에서 전력 제어를 위한 게임 알고리즘)

  • Rho, Chang-Bae;Halder, N.;Song, Ju-Bin
    • Journal of Advanced Navigation Technology
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    • v.13 no.2
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    • pp.201-207
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    • 2009
  • Recently effective spectrum resource technologies have been studied using a game theorectical approach for cognitive radio networks. Radio resource management is required an effective scheme because the performance of a radio communication system much depends on it's effectiveness. In this paper, we suggest a game theoretical algorithm for adaptive power control which is required an effect scheme in cognitive radio networks. It will be a distributed network. In the network distributed cognitive radio secondary users require an adaptive power control. There are many results which are suggested some possibility of game theoretical approaches for communication resource sharing. However, we suggest a practical game algorithm to achieve Nash equilibrium of all secondary users using a Nash equilibrium theorem in this paper. Particularly, a game model was analyzed for adaptive power control of a cognitive radio network, which is involved in DSSS (Direct Sequence Spread Spectrum) techniques. In case of K=63 and N=12 in the DSSS network, the number of iteration was less than maximum 200 using the suggested algorithm.

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Pursuit-evasion as a dynamic game

  • Imado, Fumiaki;Ichikawa, Akira;Kanai, Kimio
    • 제어로봇시스템학회:학술대회논문집
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    • 1993.10b
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    • pp.474-479
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    • 1993
  • A study about two-dimensional pursuit-evasion dynamic games is presented and discussed. A pursuer tries to intercept an evader by a strategy based on proportional navigation guidance, while the evader tries to maximize a miss distance by the optimal control. The study is applied to a ball game and an air-combat game. The results show the same features exist in both games, therefore the study will be able to apply for general two dimensional dynamic games. In the ball game, the study is extended to cases where a goal exists, while in the air-combat game, some three-dimensional problems are solved and the results are also shown.

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A Tool for the Analysis of Robot Soccer Game

  • Matko, Drago;Klancar, Gregor;Lepetic, Marko
    • International Journal of Control, Automation, and Systems
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    • v.1 no.2
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    • pp.222-228
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    • 2003
  • A tool which can be used for the analysis of a robot soccer game is presented. The tool enables automatic filtering and selection of game sequences which are suitable for the analysis of the game. Fuzzy logic is used since the data gathered by a camera is highly noisy. The data used in the paper was recorded during the game Germany - Slovenia in Hagen, on November 11, 2001. The dynamic parameters of our robots are estimated using the least squares technique. Meandering parameters are estimated and an attempt is made to identify the strategy of the opposing team with the method of introspection.

A Management method of Load Balancing among Game Servers based on Distributed Server System Using Map Balance Server (분산형 서버 구조 기반 Map 밸런스 서버를 이용한 게임 서버 간 부하 관리 방법)

  • Kim, Soon-Gohn;Lee, Nam-Jae;Yang, Seung-Weon
    • Journal of Advanced Navigation Technology
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    • v.15 no.6
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    • pp.1034-1041
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    • 2011
  • Generally, In distributed online game server system, game maps are processed separately by means of dividing into several unit blocks. But the keeping normal distribution of user in game map is very difficult because preferences of game users are not same according to individual user's private character. For this reason, if the huge number of users concentrate on particular region of same game map at once, the game server exceed their threshold so that the system can be getting down. Conversely, the efficiency of system goes down considerably because the game server must perform map processing continuously even under user_empty situation. To solve this problem, in this paper, we propose a Map management method to control relatively normal distribution of users in game maps using Map Balance Server. In suggested model, we can reduce the load of game servers by means of turn off the game map processing temporary when a server is under user_empty situation. we also can maximize server performance by means of redistribution of map processing load among servers.

미분 게임에서 유전자 알고리즘을 이용한 유도 규칙 산출에 대한 연구

  • 김용운;박동조
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.359-362
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    • 1996
  • The guidance system which uses the line-of-sight(LOS) rate to guide the missile towards its target has been used to the conventional differential game, such as the pursuer-evader game. Proportional navigation guidance and its derivatives have been shown to be an effective LOS rate guidance system. In this paper, we have used the genetic algorithm to construct the guidance system for the pursuer-evader type differential game. Also we have proposed the prediction model to obtain the informations about the intention of future actions of the pursuer and the evader.

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Time-varying Proportional Navigation Guidance using Deep Reinforcement Learning (심층 강화학습을 이용한 시변 비례 항법 유도 기법)

  • Chae, Hyeok-Joo;Lee, Daniel;Park, Su-Jeong;Choi, Han-Lim;Park, Han-Sol;An, Kyeong-Soo
    • Journal of the Korea Institute of Military Science and Technology
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    • v.23 no.4
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    • pp.399-406
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    • 2020
  • In this paper, we propose a time-varying proportional navigation guidance law that determines the proportional navigation gain in real-time according to the operating situation. When intercepting a target, an unidentified evasion strategy causes a loss of optimality. To compensate for this problem, proper proportional navigation gain is derived at every time step by solving an optimal control problem with the inferred evader's strategy. Recently, deep reinforcement learning algorithms are introduced to deal with complex optimal control problem efficiently. We adapt the actor-critic method to build a proportional navigation gain network and the network is trained by the Proximal Policy Optimization(PPO) algorithm to learn an evasion strategy of the target. Numerical experiments show the effectiveness and optimality of the proposed method.