• 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.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.474-477
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• 1996

In this paper, a numerical method is developed to solve the 2 dimensional missile/target persuit-evasion game. The numerical solver for the problem is composed of two parts: parametrization of the kinematic equations of motion using collocation and optimization of the parametrized minimax problem using a nonlinear programming. A numerical example is solved to verify the performance of the proposed numerical scheme.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.946-948
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• 1996

In this paper, we consider a 2-dimensional pursuit-evasion game between a maneuvering target and a coasting missile using qualitative game theory. The optimal evasion algorithm of the target and the optimal guidance algorithm of the missile are determined and the barrier trajectories of this game are obtained through computer simulation. The optimal strategy of the missile and target is to turn toward the final line of sight direction using maximum input and maintain its direction. The capture set of the missile can be obtained by backward integration from the BUP.

• The KIPS Transactions:PartB
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• v.15B no.3
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• pp.253-258
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• 2008

Recently, game players want new game requiring more various tactics and strategies in the complex environment beyond simple and repetitive play. Various artificial intelligence techniques have been suggested to make the game characters learn within this environment, and the recent researches include the neural network and the genetic algorithm. The Genetic programming(GP) has been used in this study for learning strategy of the agent in the pursuit-evasion problem which is used widely in the game theories. The suggested GP algorithm is faster than the existing algorithm such as neural network, it can be understood instinctively, and it has high adaptability since the evolving chromosomes can be transformed to the reasoning rules.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.156.3-156
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• 2001

This paper handles synthesis and investigation of a neural network guidance law based on pursuit-evasion games. This work considers two-dimensional pursuit-evasion games solved by using the gradient method. The procedure of developing a guidance law from the game-optimal solutions is deeply examined, and important features of the neural network guidance are investigated. The proposed neural network guidance law takes the range, range rate, line-of-sight rate, and heading error as its input variables. By reconstructing the trajectory, the accuracy of the neural network approximation is verified. Afterwards, robustness of the neural network guidance to the autopilot lag, which results from its feedback structure, is investigated ...

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.213-215
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• 1995

This paper is concerned with a coplanar pursuit-evasion game of one inertial evader and two identical noninertial pursuers. The terminal time is fired and the payoff is the distance between the evader and the nearest pursuer when tile game is terminated. The value functions and the strategies is constructed for all the game surface. To get a value function, we use the generalization of the Bellman-Isaacs fundamental equation.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.3
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• pp.215-221
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• 2012

In this paper, we introduce an optimization method to improve pursuit performance of a pursuer in a pursuit-evasion game (PEG). Pursuers build a probability map and employ a hybrid pursuit policy which combines the merits of local-max and global-max pursuit policies to search and capture evaders as soon as possible in a 2-dimensional space. We propose an episodic parameter optimization (EPO) algorithm to learn good values for the weighting parameters of a hybrid pursuit policy. The EPO algorithm is performed while many episodes of the PEG are run repeatedly and the reward of each episode is accumulated using reinforcement learning, and the candidate weighting parameter is selected in a way that maximizes the total averaged reward by using the golden section search method. We found the best pursuit policy in various situations which are the different number of evaders and the different size of spaces and analyzed results.

• Bulletin of the Korean Mathematical Society
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• v.57 no.1
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• pp.127-131
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• 2020

We discuss two unrelated topics regarding Cops and Robbers, a well-known pursuit-evasion game played on a simple graph. First, we address a recent question of Breen et al. and prove the PSPACE-completeness of the cop throttling number, that is, the minimal possible sum of the number k of cops and the number capt(k) of moves that the robber can survive against k cops under the optimal play of both sides. Secondly, we revisit a teleporting version of the game due to Wagner; we disprove one of his conjectures and suggest a new related research problem.