• Journal of Communications and Networks
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• v.18 no.3
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• pp.411-419
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• 2016

This article investigates the problem of distributed channel selection in opportunistic spectrum access networks from a perspective of interference minimization. The traditional physical (PHY)-layer interference model is for information theoretic analysis. When practical multiple access mechanisms are considered, the recently developed binary medium access control (MAC)-layer interference model in the previous work is more useful, in which the experienced interference of a user is defined as the number of competing users. However, the binary model is not accurate in mathematics analysis with poor achievable performance. Therefore, we propose a real-valued one called stochastic MAC-layer interference model, where the utility of a player is defined as a function of the aggregate weight of the stochastic interference of competing neighbors. Then, the distributed channel selection problem in the stochastic MAC-layer interference model is formulated as a weighted stochastic MAC-layer interference minimization game and we proved that the game is an exact potential game which exists one pure strategy Nash equilibrium point at least. By using the proposed stochastic learning-automata based uncoupled algorithm with heterogeneous learning parameter (SLA-H), we can achieve suboptimal convergence averagely and this result can be verified in the simulation. Moreover, the simulated results also prove that the proposed stochastic model can achieve higher throughput performance and faster convergence behavior than the binary one.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.7
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• pp.2454-2467
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• 2015

Increasing traffic and bandwidth requirements bring challenges to the next generation wireless networks (5G). As one of the main technology in 5G networks, Ultra-Dense Network (UDN) can be used to improve network coverage. In this paper, a radio over fiber based model is proposed to solve the load balancing problem in ultra-dense network. Stochastic differential game is introduced for the load balancing algorithm, and optimal load allocated to each access point (RAP) are formulated as Nash Equilibrium. It is proved that the optimal load can be achieved and the stochastic differential game based scheme is applicable and acceptable. Numerical results are given to prove the effectiveness of the optimal algorithm.

• Journal of the Korean Operations Research and Management Science Society
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• v.3 no.2
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• pp.41-45
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• 1978

Duel models are frequently used in war game simulation. Both game-theoretic approach and stochastic approach are applied to duel situations in war game. Game-theoretic models are usually classified into three categories, noisy duel, silent duel, and duel of continuous firing. Stochastic duels are classified depending upon assumptions. In this paper formulation and a general solution for each model will be summarized.

• Journal of Platform Technology
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• v.9 no.1
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• pp.3-14
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• 2021

Cognitive Radio network (CR) is a promising paradigm that helps the unlicensed user (Secondary User) to analyse the spectrum and coordinate the spectrum access to support the creation of common control channel (CCC). The cooperation of secondary users and broadcasting between them is done through transmitting messages in CCC. In case, if the control channels may get jammed and it may directly degrade the network's performance and under such scenario jammers will devastate the control channels. Hopping sequences may be one of the predominant approaches and it may be used to fight against this problem to confront jammer. The jamming attack can be alleviated using one of the game modelling approach and in this proposed scheme stochastic games has been analysed with more single users to provide the flexible control channels against intrusive attacks by mentioning the states of each player, strategies ,actions and players reward. The proposed work uses a modern player action and better strategic view on game theoretic modelling is stochastic game theory has been taken in to consideration and applied to prevent the jamming attack in CR network. The selection of decision is based on Q learning approach to mitigate the jamming nodes using the optimal MDP decision process

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1426-1447
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• 2021

The payoff game between task publishers and users in the mobile crowdsensing environment is a hot topic of research. A optimal payoff selection model based on stochastic evolutionary game is proposed. Firstly, the process of payoff optimization selection is modeled as a task publisher-user stochastic evolutionary game model. Secondly, the low-quality data is identified by the data quality evaluation algorithm, which improves the fitness of perceptual task matching target users, so that task publishers and users can obtain the optimal payoff at the current moment. Finally, by solving the stability strategy and analyzing the stability of the model, the optimal payoff strategy is obtained under different intensity of random interference and different initial state. The simulation results show that, in the aspect of data quality evaluation, compared with BP detection method and SVM detection method, the accuracy of anomaly data detection of the proposed model is improved by 8.1% and 0.5% respectively, and the accuracy of data classification is improved by 59.2% and 32.2% respectively. In the aspect of the optimal payoff strategy selection, it is verified that the proposed model can reasonably select the payoff strategy.

• Journal of Korea Game Society
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• v.2 no.2
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• pp.52-59
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• 2002

This paper introduces FSM, statistical FSM and NFA that are used for assigning behaviors of NPCs in computer games. We propose a new method for remedy of the weakness of previous studies. We use the method of inferencing stochastic grammars to generate NPCs behaviors. Using this method we can generate a lot of MPCs or Computer Players behaviors automatically and the games will be more enjoyable.

• Journal of Korea Game Society
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• v.16 no.3
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• pp.77-86
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• 2016

As the focus of game market moves to mobile era, payment on cyber money, specifically for Gacha system, possesses a large portion for creating profit in game industry. For this reason, this study mainly focuses on Puzzle and Dragon, the mobile game of Gungho online entertainment in Japan, which has made enormous profit for several years. The analysis on consumer sentiment for Gacha are categorized as below: (1) gambling mentality and cognitive error in stochastic game in God festival (2) reactional psychology for scarcity message in limited time God festival and collaboration (3) personal satisfaction through friend system and character collection.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.5820-5834
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• 2017

This paper investigates the channel selection problem with dynamic users and the asymmetric interference relation in distributed opportunistic spectrum access systems. Since users transmitting data are based on their traffic demands, they dynamically compete for the channel occupation. Moreover, the heterogeneous interference range leads to asymmetric interference relation. The dynamic users and asymmetric interference relation bring about new challenges such as dynamic random systems and poor fairness. In this article, we will focus on maximizing the tradeoff between the achievable utility and access cost of each user, formulate the channel selection problem as a directional graphical game and prove it as an exact potential game presenting at least one pure Nash equilibrium point. We show that the best NE point maximizes both the personal and system utility, and employ the stochastic learning approach algorithm for achieving the best NE point. Simulation results show that the algorithm converges, presents near-optimal performance and good fairness, and the directional graphical model improves the systems throughput performance in different asymmetric level systems.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.7
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• pp.315-320
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• 2017

In this paper, I design a new scheme that is immune to malicious attack based on the weighted voting game. By using stochastic learning, the proposed scheme can revoke the certification of malicious node. Through the revocation process, the proposed scheme can effectively adapt the dynamic Mobile Ad hoc network situation. Simulation results clearly indicate that the developed scheme has better performance than other existing schemes under widely diverse network environments.

• Smart Media Journal
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• v.9 no.4
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• pp.36-43
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• 2020

The Monte Carlo tree search (MCTS) is a popular method for implementing an intelligent game program. It has several hyper-parameters that require an optimization for showing the best performance. Due to the stochastic nature of the MCTS, the hyper-parameter optimization is difficult to solve. This paper uses the self-playing capability of the MCTS-based game program for optimizing the hyper-parameters. It seeks a winner path over the hyper-parameter space while performing the self-play. The top-q longest winners in the winner path compete for the final winner. The experiment using the 15-15-5 game (Omok in Korean name) showed a promising result.