Possibility Clustering Algorithm for Incomplete Data Based on a Deep Computing Model

2021 ◽  
pp. 2141012
Author(s):  
Dongping Li ◽  
Yingchun Yang ◽  
Qiang Yue ◽  
Liqi Cheng ◽  
Jie Song ◽  
...  
Keyword(s):  
Game Theory ◽  
Incomplete Data ◽  
Data Analytics ◽  
Clustering Algorithm ◽  
Fundamental Theory ◽  
Computing Model ◽  
The Game Theory ◽  
The Face ◽  
Experimental Findings ◽  
Rule Out

Clustering is an essential part of data analytics and in Wireless Sensor Networks (WSN). It becomes a problem for causes such as insufficient, unavailable, or compromised data in the face of uncertainties. A solution to tackle the instability of clusters due to missed values has been proposed. The fundamental theory determines whether to incorporate an entity into a group if it is not clear and probable. One of the main issues is identifying requirements for three forms of decision definition, including an entity in a cluster, removing an object from a group, or delaying a decision (defer) to involve or rule out a group. Current studies do not adequately discuss threshold identification and use their fixed values implicitly. This work explores using the game theory-based Possibility Clustering Algorithm for Incomplete Data (PCA-ID) framework to address this problem. In specific, a game theory will be described in which thresholds are determined based on a balance between the groups’ precision and generic characteristics. The points calculated are used to elicit judgments for the grouping of unknown objects. Experimental findings on the deep learning datasets show that the PCA-ID increases the overall quality considerably while maintaining comparable precision levels in competition with similar systems.

scholarly journals Computing Unloading Strategy of Massive Internet of Things Devices Based on Game Theory in Mobile Edge Computing

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Xinhui Ding ◽  
Wenjuan Zhang
Keyword(s):  
Game Theory ◽  
Energy Consumption ◽  
Internet Of Things ◽  
Transmission Rate ◽  
Mobile User ◽  
Edge Computing ◽  
Communication Model ◽  
Mobile Edge Computing ◽  
Computing Model ◽  
The Game Theory

Due to the limited computing resources of the mobile edge computing (MEC) server, a massive Internet of things device computing unloading strategy using game theory in mobile edge computing is proposed. First of all, in order to make full use of the massive local Internet of things equipment resources, a new MEC system computing an unloading system model based on device-to-device (D2D) communication is designed and modeled, including communication model, task model, and computing model. Then, by using the utility function, the parameters are substituted into it, and the optimization problem with the goal of maximizing the number of CPU cycles and minimizing the energy consumption is constructed with the unloading strategy and power as constraints. Finally, the game theory is used to solve the problem of computing offload. Based on the proposed beneficial task offload theory, combined with the mobile user device computing offload task amount, transmission rate, idle device performance, and other factors, the computing offload scheme suitable for their own situation is selected. The simulation results show that the proposed scheme has better convergence characteristics, and, compared with other schemes, the proposed scheme significantly improves the amount of data transmission and reduces the energy consumption of the task.

Penilaian Kinerja Dosen Dengan Menggunakan Metode AHP Studi Kasus di STIE Ahmad Dahlan Jakarta

Liquidity ◽  
2018 ◽  
Vol 2 (1) ◽  
pp. 100-109
Author(s):  
Ellya Sestri
Keyword(s):  
Decision Making ◽  
Performance Appraisal ◽  
Technological Progress ◽  
Pairwise Comparison ◽  
Relative Importance ◽  
Faculty Performance ◽  
Business World ◽  
The Face ◽  
Hierarchy Process ◽  
Rule Out

An increasingly rapid technological progress in the era of globalization in the business world, so do not rule out the possibility that a decision-making is something that is very vital in determining the decisions to be taken in the face of competitive business world. Decision making can be influenced by several aspects, this can affect the speed of decision making by the decision maker in which decisions must be quick and accurate. Lecturer Performance Assessment Using the Analytical Hierarchy Process is a decision support system that aims to assess faculty performance according to certain criteria. This system of faculty performance appraisal criteria to map a hierarchy, where each hierarchy will be performed pairwise comparison, the pairwise comparisons between criteria, so to get a comparison of the relative importance of criteria with each other. The results of this comparison is then analyzed to obtain the priority of each criterion. Once completed and performed an assessment of alternative options to be compared and calculated to obtain the best alternatives according to established criteria.

Reputation and Gossip in Game Theory

2019 ◽  
pp. 213-229
Author(s):  
Charles Roddie
Keyword(s):  
Game Theory ◽  
Strategic Behavior ◽  
Third Party ◽  
The Past ◽  
Past Behavior ◽  
Future Behavior ◽  
The Game Theory ◽  
Shed Light

When interacting with others, it is often important for you to know what they have done in similar situations in the past: to know their reputation. One reason is that their past behavior may be a guide to their future behavior. A second reason is that their past behavior may have qualified them for reward and cooperation, or for punishment and revenge. The fact that you respond positively or negatively to the reputation of others then generates incentives for them to maintain good reputations. This article surveys the game theory literature which analyses the mechanisms and incentives involved in reputation. It also discusses how experiments have shed light on strategic behavior involved in maintaining reputations, and the adequacy of unreliable and third party information (gossip) for maintaining incentives for cooperation.

scholarly journals The Superiority of Quantum Strategy in 3-Player Prisoner’s Dilemma

Mathematics ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1443
Author(s):  
Zhiyuan Dong ◽  
Ai-Guo Wu
Keyword(s):  
Game Theory ◽  
Prisoner's Dilemma ◽  
Prisoner’S Dilemma ◽  
Quantum Game ◽  
Final State ◽  
The Game Theory ◽  
Initial States ◽  
Quantum Strategy ◽  
Selection Of

In this paper, we extend the quantum game theory of Prisoner’s Dilemma to the N-player case. The final state of quantum game theory of N-player Prisoner’s Dilemma is derived, which can be used to investigate the payoff of each player. As demonstration, two cases (2-player and 3-player) are studied to illustrate the superiority of quantum strategy in the game theory. Specifically, the non-unique entanglement parameter is found to maximize the total payoff, which oscillates periodically. Finally, the optimal strategic set is proved to depend on the selection of initial states.

scholarly journals Multi-Robot Searching using Game-Theory Based Approach

10.5772/6232 ◽  
2008 ◽  
Vol 5 (4) ◽  
pp. 44 ◽  
Author(s):  
Yan Meng
Keyword(s):  
Game Theory ◽  
Dynamic Programming ◽  
Utility Function ◽  
Real Time ◽  
Dynamic Environment ◽  
Equilibrium Solutions ◽  
Strategy Equilibrium ◽  
The Game Theory ◽  
Target Searching ◽  
Multi Robot

This paper proposes a game-theory based approach in a multi–target searching using a multi-robot system in a dynamic environment. It is assumed that a rough priori probability map of the targets' distribution within the environment is given. To consider the interaction between the robots, a dynamic-programming equation is proposed to estimate the utility function for each robot. Based on this utility function, a cooperative nonzero-sum game is generated, where both pure Nash Equilibrium and mixed-strategy Equilibrium solutions are presented to achieve an optimal overall robot behaviors. A special consideration has been taken to improve the real-time performance of the game-theory based approach. Several mechanisms, such as event-driven discretization, one-step dynamic programming, and decision buffer, have been proposed to reduce the computational complexity. The main advantage of the algorithm lies in its real-time capabilities whilst being efficient and robust to dynamic environments.

scholarly journals K-Nearest Neighbor Intervals Based AP Clustering Algorithm for Large Incomplete Data

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Cheng Lu ◽  
Shiji Song ◽  
Cheng Wu
Keyword(s):  
Clustering Analysis ◽  
Incomplete Data ◽  
Clustering Algorithm ◽  
Nearest Neighbor ◽  
Interval Data ◽  
Similarity Function ◽  
K Nearest Neighbor ◽  
Partial Data ◽  
Missing Attributes ◽  
Ap Clustering

The Affinity Propagation (AP) algorithm is an effective algorithm for clustering analysis, but it can not be directly applicable to the case of incomplete data. In view of the prevalence of missing data and the uncertainty of missing attributes, we put forward a modified AP clustering algorithm based onK-nearest neighbor intervals (KNNI) for incomplete data. Based on an Improved Partial Data Strategy, the proposed algorithm estimates the KNNI representation of missing attributes by using the attribute distribution information of the available data. The similarity function can be changed by dealing with the interval data. Then the improved AP algorithm can be applicable to the case of incomplete data. Experiments on several UCI datasets show that the proposed algorithm achieves impressive clustering results.

Application of Game Theory for Big Data Analytics

2018 ◽  
pp. 199-210
Author(s):  
Mohammad Muhtady Muhaisin ◽  
Taseef Rahman
Keyword(s):  
Game Theory ◽  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics

scholarly journals Cooperative n-person Prisoner's Dilemma on a Network

2021 ◽  
Vol 14 ◽  
pp. 122-126
Author(s):  
Aleksandra L. Grinikh ◽  
◽  
Leon A. Petrosyan ◽  
Keyword(s):  
Game Theory ◽  
Cooperative Game ◽  
Prisoner's Dilemma ◽  
Prisoner’S Dilemma ◽  
Pairwise Interaction ◽  
Network Interaction ◽  
The Game Theory

In the paper n-person prisoner's dilemma on the network is investigated. A cooperative game with the pairwise interaction of players is constructed. The model is a modification of the classic 2-person prisoner's dilemma problem in the game theory. Network interaction provide an ability to take into account the in uence only to the adjacent players from the whole set of players. The feature of the game is found that allows to make a decision about necessity of playing dominated strategy by a few players. This solution is based on the number of the adjacent players. The work is a continuation of the paper published earlier by Grinikh A.L. and Petrosyan L.A. in 2021.

scholarly journals Effective decisions for individualized assessment and minimization of the risk of unfriendly takeover of enterprises: the features of the game theory application

2019 ◽  
Vol 17 (1) ◽  
pp. 370-379
Author(s):  
Oksana Korolovych ◽  
Olha Chabaniuk ◽  
Natalia Ostapiuk ◽  
Yurii Kotviakovskyi ◽  
Nelia Gut
Keyword(s):  
Game Theory ◽  
External Environment ◽  
Point Of View ◽  
Control Moment ◽  
The Game Theory ◽  
Antagonistic Game ◽  
Target Company ◽  
Legislative Framework ◽  
Theory Application ◽  
Detailed Assessment

The conditions for doing business at this stage are often similar in a game in which you need to calculate your actions a few steps ahead. At the same time, it is important to highlight several possible current options and make the necessary decision at the control moment. Moreover, each of the options formed should be justified, understandable and take into account the risk factors and available resources.Today, the main problem of assessing and minimizing the risk of “unfriendly takeover” is due to the fact that in most cases the raider is a player who acts quite legitimately and relies on the loopholes of the current legislative framework. Therefore, it is easier to identify possible actions of the raider and to avoid them within the limits of the reverse game than to deal with the consequences.The purpose of the research is to study the specificity of the individualized assessment and minimization of the risk of “unfriendly takeover” by using elements of game theory.It has been taken into account that the effect of individualization in assessing the risk of unfriendly takeover of enterprises can possibly be achieved on the basis of the application of game theory, the elements of which provide simulation of the unfriendly takeover process within the mathematical description of the inherent combinations of attack/defence as if they actually occurred in time both within one state of the external environment and for their given set.The results allowed forming mathematical decision-making models based on the elements of the antagonistic game “raider-target enterprise” and “raider games with the external environment”, which proved the possibility to: 1) identify possible functions of wins/losses; 2) combinations of attacks that can be neglected (that is, from the point of view of the rationality of decisions, will be rejected by the raider); 3) the ranking of the raider’s “attack combinations” for the reliability of their use during “unfriendly takeover”. Under such conditions, the target company can provide not only a detailed assessment, but also an effective minimization of the risk of “unfriendly takeover” and allocate the best combination of protection.

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