• International Journal of Control, Automation, and Systems
• /
• v.2 no.4
• /
• pp.463-474
• /
• 2004

Game theory is a method of mathematical analysis developed to study the decision making process. In 1928, Von Neumann mathematically proved that every two-person, zero-sum game with many pure finite strategies for each player is deterministic. In the early 50's, Nash presented another concept as the basis for a generalization of Von Neumann's theorem. Another central achievement of game theory is the introduction of evolutionary game theory, by which agents can play optimal strategies in the absence of rationality. Through the process of Darwinian selection, a population of agents can evolve to an Evolutionary Stable Strategy (ESS) as introduced by Maynard Smith in 1982. Keeping pace with these game theoretical studies, the first computer simulation of coevolution was tried out by Hillis. Moreover, Kauffman proposed the NK model to analyze coevolutionary dynamics between different species. He showed how coevolutionary phenomenon reaches static states and that these states are either Nash equilibrium or ESS in game theory. Since studies concerning coevolutionary phenomenon were initiated, there have been numerous other researchers who have developed coevolutionary algorithms. In this paper we propose a new coevolutionary algorithm named Game theory based Coevolutionary Algorithm (GCEA) and we confirm that this algorithm can be a solution of evolutionary problems by searching the ESS. To evaluate this newly designed approach, we solve several test Multiobjective Optimization Problems (MOPs). From the results of these evaluations, we confirm that evolutionary game can be embodied by the coevolutionary algorithm and analyze the optimization performance of our algorithm by comparing the performance of our algorithm with that of other evolutionary optimization algorithms.

• Journal of Korea Game Society
• /
• v.9 no.2
• /
• pp.41-50
• /
• 2009

The convergence paradigm that appears with the integrated media environment has effect on digital storytelling using digital technology, then 'Trans-media storytelling' which is a new form of digital storytelling makes gradual expand its scope. This study focused on the Alternative Reality Game which adopt trans-media storytelling in the game genre. This paper interpreted the idea of ARG on comparing different forms of ARG and existing games and the distinctive features of ARG storytelling which is blurring the line between real and virtual on the Simulation theory. This is a valuable study for understanding the new storytelling form within the media convergence and developing the digital storytelling in the future.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.35 no.2B
• /
• pp.269-278
• /
• 2010

In the clustering protocol, lifetime of the cluster members radically decrease because frequency interference between clusters make every cluster member consume a lot of energy to maintain or increase its transmission rate. In this paper, we analyze the frequency interference among the clusters with the game theory which deals with resource bargaining problems between players, and present a rational power allocation strategy. Both the cases that each cluster tries to selfishly occupy and cooperatively share the resource are analyzed in terms of non-cooperative and cooperative games. In simulation, we compare the cooperative game with non-cooperative game in terms of the node lifetime.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.42 no.4
• /
• pp.39-48
• /
• 2019

This paper considers the Prisoner's Dilemma Game in which there exists a dilemma that the best response is that both players are to confess, but doing not confess can give a higher gain to the both players in a social perspective. To resolve such a dilemma in the game, an incentive model to encourage to confess and a penalty model for being imposed when not confessing are introduced, respectively. Then, the conditions are characterized under which incentive or penalty involved in the game's payoffs can make the game rational without a dilemma on both the personal and social perspectives, by taking the payoff values as variables with the incentive and penalty factors. Furthermore, it turns out that the resulting values of incentive and penalty are inversely proportional to each other, and thus, obtaining one of these amounts can provide the other. Simple examples are shown to interpret the theoretical verifications of our models, and randomly generated data based simulation results investigate the tendency of incentive and penalty and the resulting game values for a variety of instances. These results can provide a framework on resolving the dilemma by artificially putting incentive or penalty, although it is careful to apply more generalized real world games.

• Journal of Korea Game Society
• /
• v.13 no.6
• /
• pp.43-52
• /
• 2013

Path finder is one of the very important algorithm of artificial intelligence and is a process generally used in many game fields. Path finder requires many calculation, so it exerts enormous influences on performances. To solve this, many researches on the ways to reduce the amount of calculate operations have been made, and the typical example is A* algorithm but it has unnecessary computing process, reducing efficiency. In this paper, to reduce the amount of calculate operations such as node search with costly arithmetic operations, we proposes the weight based pre-processing A* algorithm. The simulation was materialized to measure the efficiency of the weight based pre-process A* algorithm, and the results of the experiments showed that the weight based method was approximately 1~2 times more efficient than the general methods.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.10
• /
• pp.3789-3809
• /
• 2015

In this paper, we deal with the problem of M2M gateways' network selection for different types of M2M traffic in heterogeneous wireless networks. Based on the difference in traffic's quality of service (QoS) requirements, the M2M traffic produced by various applications is mainly classified as two categories: flexible traffic and rigid traffic. Then, game theory is adopted to solve the problem of network-channel selection with the coexistence of flexible and rigid traffic, named as flexible network access (FNA). We prove the formulated discrete game is a potential game. The existence and feasibility of the Nash equilibrium (NE) of the proposed game are also analyzed. Then, an iterative algorithm based on optimal reaction criterion and a distributed algorithm with limited feedback based on learning automata are presented to obtain the NE of the proposed game. In simulations, the proposed iterative algorithm can achieve a near optimal sum utility of whole network with low complexity compared to the exhaustive search. In addition, the simulation results show that our proposed algorithms outperform existing methods in terms of sum utility and load balance.

• Journal of Korea Game Society
• /
• v.5 no.1
• /
• pp.41-44
• /
• 2005

This paper is model can be useful and capable of automatically collecting and classifying the various information about a wide range of security incidents such as hackings, worms, spyware, cyber-terror, network espionage and information warfare from firewall, IDS, VPN and so on. According to them Internet game and an automated/integrated computer emergency response system can perform an attack assessment and an early warning for any incidents based on Enterprise Security Management environment.

• ETRI Journal
• /
• v.40 no.1
• /
• pp.61-71
• /
• 2018

In this study, we developed hybrid control algorithms in smart base stations (SBSs) along with devised communication, caching, and computing techniques. In the proposed scheme, SBSs are equipped with computing power and data storage to collectively offload the computation from mobile user equipment and to cache the data from clouds. To combine in a refined manner the communication, caching, and computing algorithms, game theory is adopted to characterize competitive and cooperative interactions. The main contribution of our proposed scheme is to illuminate the ultimate synergy behind a fully integrated approach, while providing excellent adaptability and flexibility to satisfy the different performance requirements. Simulation results demonstrate that the proposed approach can outperform existing schemes by approximately 5% to 15% in terms of bandwidth utilization, access delay, and system throughput.

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

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.10
• /
• pp.4177-4190
• /
• 2015

Current research on Internet of Things (IoT) has primarily addressed the means to enhancing smart resource allocation, automatic network operation, and secure service provisioning. In particular, providing satisfactory security service in IoT systems is indispensable to its mission critical applications. However, limited resources prevent full security coverage at all times. Therefore, these limited resources must be deployed intelligently by considering differences in priorities of targets that require security coverage. In this study, we have developed a new application of Cognitive Radio (CR) technology for IoT systems and provide an appropriate security solution that will enable IoT to be more affordable and applicable than it is currently. To resolve the security-related resource allocation problem, game theory is a suitable and effective tool. Based on the Blotto game model, we propose a new strategic power allocation scheme to ensure secure CR communications. A simulation shows that our proposed scheme can effectively respond to current system conditions and perform more effectively than other existing schemes in dynamically changeable IoT environments.