Author Search Result

[Author] Ha Ryoung OH(3hit)

1-3hit
  • Satisfiability Testing for Non-clausal Propositional Calculus by Using Petri Nets

    Won Ho CHUNG  Ha Ryoung OH  Myunghwan KIM  

     
    PAPER-Graphs and Networks

      Vol:
    E73-E No:4
      Page(s):
    539-544

    Petri net based satisfiability testing for non-clausal propositional calculus is presented. Every formula in propositional calculus is hierarchically represented by an acyclic free-choice Petri net called logic Petri net. Then a logic Petri net is combined with two way alternating modules, whose number depends upon the number of atoms used in the formula. It is shown that the satisfiability of a formula with non-clausal form can be tested by obtaining reachable firing set of the complete logic Petri net corresponding to the formula under the maximum firing rule.

  • Exploiting Intelligence in Fighting Action Games Using Neural Networks

    Byeong Heon CHO  Sung Hoon JUNG  Yeong Rak SEONG  Ha Ryoung OH  

     
    PAPER-Biocybernetics, Neurocomputing

      Vol:
    E89-D No:3
      Page(s):
    1249-1256

    This paper proposes novel methods to provide intelligence for characters in fighting action games by using neural networks. First, how a character learns basic game rules and matches against randomly acting opponents is considered. Since each action takes more than one time unit in general fighting action games, the results of a character's action are exposed not immediately but several time units later. We evaluate the fitness of a decision by using the relative score change caused by the decision. Whenever the scores of fighting characters are changed, the decision causing the score change is identified, and then the neural network is trained by using the score difference and the previous input and output values which induced the decision. Second, how to cope more properly with opponents that act with predefined action patterns is addressed. The opponents' past actions are utilized to find out the optimal counter-actions for the patterns. Lastly, a method in order to learn moving actions is proposed. To evaluate the performance of the proposed algorithm, we implement a simple fighting action game. Then the proposed intelligent character (IC) fights with the opponent characters (OCs) which act randomly or with predefined action patterns. The results show that the IC understands the game rules and finds out the optimal counter-actions for the opponents' action patterns by itself.

  • A Distributed Mutual Exclusion Algorithm Based on Weak Copy Consistency

    Seoung Sup LEE  Ha Ryoung OH  June Hyoung KIM  Won Ho CHUNG  Myunghwan KIM  

     
    PAPER-Computer Networks

      Vol:
    E75-D No:3
      Page(s):
    298-306

    This paper presents a destributed algorithm that uses weak copy consistency to create mutual exclusion in a distributed computer system. The weak copy consistency is deduced from the uncertainty of state which occurs due to the finite and unpredictable communication delays in a distributed environment. Also the method correlates outdated state information to current state. The average number of messages to enter critical section in the algorithm is n/2 to n messages where n is the number of sites. We show that the algorithm achieves mutual exclusion and the fairness and liveness of the algorithm is proven. We study the performance of the algorithm by simulation technique.

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