scholarly journals A Dynamic Territorializing Approach for Multiagent Task Allocation

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Mohammad Islam ◽  
Mehdi Dadvar ◽  
Hassan Zargarzadeh
Keyword(s):  
Task Allocation ◽  
Center Of Mass ◽  
Theoretic Analysis ◽  
Game Theoretic Analysis ◽  
Alternative Approach ◽  
Game Theoretic ◽  
Simulation Results ◽  
Reasoning Mechanism

In this paper, we propose a dynamic territorializing approach for the problem of distributing tasks among a group of robots. We consider the scenario in which a task comprises two subtasks—detection and completion; two complementary teams of agents, hunters and gatherers, are assigned for the subtasks. Hunters are assigned with the task of exploring the environment, i.e., detection, whereas gatherers are assigned with the latter subtask. To minimize the workload among the gatherers, the proposed algorithm utilizes the center of mass of the known targets to form territories among the gatherers. The concept of center of mass has been adopted because it simplifies the task of territorial optimization and allows the system to dynamically adapt to changes in the environment by adjusting the assigned partitions as more targets are discovered. In addition, we present a game-theoretic analysis to justify the agents’ reasoning mechanism to stay within their territory while completing the tasks. Moreover, simulation results are presented to analyze the performance of the proposed algorithm. First, we investigate how the performance of the proposed algorithm varies as the frequency of territorializing is varied. Then, we examine how the density of the tasks affects the performance of the algorithm. Finally, the effectiveness of the proposed algorithm is verified by comparing its performance against an alternative approach.

scholarly journals A Game-Theoretic Analysis for Distributed Honeypots

2019 ◽  
Vol 11 (3) ◽  
pp. 65 ◽  
Author(s):  
Yang Li ◽  
Leyi Shi ◽  
Haijie Feng
Keyword(s):  
Game Theory ◽  
Network Security ◽  
Dynamic Properties ◽  
System Configuration ◽  
Theoretic Analysis ◽  
Property A ◽  
Game Theoretic Analysis ◽  
Innovative System ◽  
Game Theoretic ◽  
Simulation Results

A honeypot is a decoy tool for luring an attacker and interacting with it, further consuming its resources. Due to its fake property, a honeypot can be recognized by the adversary and loses its value. Honeypots equipped with dynamic characteristics are capable of deceiving intruders. However, most of their dynamic properties are reflected in the system configuration, rather than the location. Dynamic honeypots are faced with the risk of being identified and avoided. In this paper, we focus on the dynamic locations of honeypots and propose a distributed honeypot scheme. By periodically changing the services, the attacker cannot distinguish the real services from honeypots, and the illegal attack flow can be recognized. We adopt game theory to illustrate the effectiveness of our system. Gambit simulations are conducted to validate our proposed scheme. The game-theoretic reasoning shows that our system comprises an innovative system defense. Further simulation results prove that the proposed scheme improves the server’s payoff and that the attacker tends to abandon launching attacks. Therefore, the proposed distributed honeypot scheme is effective for network security.

scholarly journals A game theoretic approach reveals that discretizing clinical information can reduce antibiotic misuse

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Maya Diamant ◽  
Shoham Baruch ◽  
Eias Kassem ◽  
Khitam Muhsen ◽  
Dov Samet ◽  
...  
Keyword(s):  
Antibiotic Prescription ◽  
Clinical Information ◽  
Social Optimum ◽  
Theoretic Approach ◽  
Theoretic Analysis ◽  
Game Theoretic Analysis ◽  
Optimal Output ◽  
The Social ◽  
Game Theoretic ◽  
Game Theoretic Approach

AbstractThe overuse of antibiotics is exacerbating the antibiotic resistance crisis. Since this problem is a classic common-goods dilemma, it naturally lends itself to a game-theoretic analysis. Hence, we designed a model wherein physicians weigh whether antibiotics should be prescribed, given that antibiotic usage depletes its future effectiveness. The physicians’ decisions rely on the probability of a bacterial infection before definitive laboratory results are available. We show that the physicians’ equilibrium decision rule of antibiotic prescription is not socially optimal. However, we prove that discretizing the information provided to physicians can mitigate the gap between their equilibrium decisions and the social optimum of antibiotic prescription. Despite this problem’s complexity, the effectiveness of the discretization solely depends on the type of information available to the physician to determine the nature of infection. This is demonstrated on theoretic distributions and a clinical dataset. Our results provide a game-theory based guide for optimal output of current and future decision support systems of antibiotic prescription.

A Game-theoretic Analysis of Hybrid Threats

2021 ◽  
pp. 1-16
Author(s):  
Pieter Balcaen ◽  
Cind Du Bois ◽  
Caroline Buts
Keyword(s):  
Theoretic Analysis ◽  
Game Theoretic Analysis ◽  
Game Theoretic ◽  
Hybrid Threats
Sign in / Sign up

Export Citation Format

Share Document