scholarly journals Channel Access-Based Joint Optimization of AoI and SINR under Attack: Game Theory and Distributed Approach

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yaoqi Yang ◽  
Xianglin Wei ◽  
Renhui Xu ◽  
Laixian Peng ◽  
Shuai Cheng ◽  
...  
Keyword(s):  
Game Theory ◽  
Optimization Problem ◽  
Channel Model ◽  
Learning Algorithm ◽  
Probability Model ◽  
Joint Optimization ◽  
Channel Access ◽  
Distributed Approach ◽  
Access Problem ◽  
The Game Theory

This paper focuses on the joint optimization of the Age of Information (AoI) and Signal to Interference plus Noise Ratio- (SINR-) oriented channel access problem under attack in the Wireless Sensor Networks (WSNs). Firstly, to overcome the uncertain, dynamic, and incomplete information constrains, an active probability model and a controlling channel model are proposed for the sensors and the receiving end, respectively. Secondly, to ensure the AoI and SINR of the data generated by the sensors when transmitted under attack, one utility function based on average AoI and SINR is defined. Then, considering the distributed feature of the channel access process, the joint optimization problem is formulated under the game theory structure. Then, a distributed learning algorithm is proposed to reach the Nash Equilibrium (NE) of the game. Finally, simulation results have verified the correctness and effectiveness of the proposed method.

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 Quit When You Can: Efficient Evaluation of Ensembles by Optimized Ordering

2021 ◽  
Vol 17 (4) ◽  
pp. 1-20
Author(s):  
Serena Wang ◽  
Maya Gupta ◽  
Seungil You
Keyword(s):  
Optimization Problem ◽  
Optimal Solution ◽  
Combinatorial Optimization Problem ◽  
Joint Optimization ◽  
Early Stopping ◽  
Time Approximation ◽  
Approximation Bound ◽  
Evaluation Time ◽  
Speed Up ◽  
Real World Problems

Given a classifier ensemble and a dataset, many examples may be confidently and accurately classified after only a subset of the base models in the ensemble is evaluated. Dynamically deciding to classify early can reduce both mean latency and CPU without harming the accuracy of the original ensemble. To achieve such gains, we propose jointly optimizing the evaluation order of the base models and early-stopping thresholds. Our proposed objective is a combinatorial optimization problem, but we provide a greedy algorithm that achieves a 4-approximation of the optimal solution under certain assumptions, which is also the best achievable polynomial-time approximation bound. Experiments on benchmark and real-world problems show that the proposed Quit When You Can (QWYC) algorithm can speed up average evaluation time by 1.8–2.7 times on even jointly trained ensembles, which are more difficult to speed up than independently or sequentially trained ensembles. QWYC’s joint optimization of ordering and thresholds also performed better in experiments than previous fixed orderings, including gradient boosted trees’ ordering.

scholarly journals Joint optimization of computing ratio and access points’ density for mixed mobile edge/cloud computing

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Tianqi Jing ◽  
Shiwen He ◽  
Fei Yu ◽  
Yongming Huang ◽  
Luxi Yang ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Coverage Probability ◽  
Optimization Problem ◽  
Mobile Cloud Computing ◽  
Low Complexity ◽  
Mixed Integer ◽  
Joint Optimization ◽  
Mobile Cloud ◽  
Convex Problem

AbstractCooperation between the mobile edge computing (MEC) and the mobile cloud computing (MCC) in offloading computing could improve quality of service (QoS) of user equipments (UEs) with computation-intensive tasks. In this paper, in order to minimize the expect charge, we focus on the problem of how to offload the computation-intensive task from the resource-scarce UE to access point’s (AP) and the cloud, and the density allocation of APs’ at mobile edge. We consider three offloading computing modes and focus on the coverage probability of each mode and corresponding ergodic rates. The resulting optimization problem is a mixed-integer and non-convex problem in the objective function and constraints. We propose a low-complexity suboptimal algorithm called Iteration of Convex Optimization and Nonlinear Programming (ICONP) to solve it. Numerical results verify the better performance of our proposed algorithm. Optimal computing ratios and APs’ density allocation contribute to the charge saving.

Decentralized Opportunistic Channel Access in CRNs Using Big-Data Driven Learning Algorithm

2021 ◽  
Vol 5 (1) ◽  
pp. 57-69
Author(s):  
Zuohong Xu ◽  
Zhou Zhang ◽  
Shilian Wang ◽  
Alireza Jolfaei ◽  
Ali Kashif Bashir ◽  
...  
Keyword(s):  
Big Data ◽  
Learning Algorithm ◽  
Data Driven ◽  
Channel Access ◽  
Opportunistic Channel Access

The smallest extraction problem

2021 ◽  
Vol 14 (11) ◽  
pp. 2445-2458
Author(s):  
Valerio Cetorelli ◽  
Paolo Atzeni ◽  
Valter Crescenzi ◽  
Franco Milicchio
Keyword(s):  
Unsupervised Learning ◽  
Optimization Problem ◽  
Learning Algorithm ◽  
State Of The Art ◽  
Data Extraction ◽  
Source Code ◽  
Web Data ◽  
Web Data Extraction ◽  
New Family ◽  
Context Free

We introduce landmark grammars , a new family of context-free grammars aimed at describing the HTML source code of pages published by large and templated websites and therefore at effectively tackling Web data extraction problems. Indeed, they address the inherent ambiguity of HTML, one of the main challenges of Web data extraction, which, despite over twenty years of research, has been largely neglected by the approaches presented in literature. We then formalize the Smallest Extraction Problem (SEP), an optimization problem for finding the grammar of a family that best describes a set of pages and contextually extract their data. Finally, we present an unsupervised learning algorithm to induce a landmark grammar from a set of pages sharing a common HTML template, and we present an automatic Web data extraction system. The experiments on consolidated benchmarks show that the approach can substantially contribute to improve the state-of-the-art.

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 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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