Adaptive Multi-Agent Control Strategy in Heterogeneous Countermeasure Environments

Author(s):  
Wei Wang ◽  
Hui Liu ◽  
Wangqun Lin

In the rapidly changing air combat environment, it is quite difficult for pilots to make speedy and reasonable decisions in a very short period due to lack of experience and the uncertainty of perception situation. Hence, the authors propose an intelligent cognitive tactical strategy framework of air combat on multi-source information in uncertain air combat situations for decision support. A fuzzy inferring tree method is proposed to simulate human intellection. Then, to further improve the accuracy of the reasoning results, a genetic algorithm is introduced to optimize the structure and parameters of fuzzy rules. The simulation results show that the proposed model is reasonable, fast, accurate, repeatable, and fatigue-free, which lays a good foundation for future high-end unmanned combat explorations.

Author(s):  
Harold R. Chamorro ◽  
Camilo Pazmino ◽  
David Paez ◽  
Fernando Jimenez ◽  
Josep M. Guerrero ◽  
...  

2021 ◽  
Author(s):  
Ilya Kovalenko ◽  
Efe Balta ◽  
Dawn Tilbury ◽  
Kira Barton

Due to the advancements in manufacturing system technology and the ever-increasing demand for personalized products, there is a growing desire to improve the flexibility of manufacturing systems. Multi-agent control is one strategy that has been proposed to address this challenge. The multi-agent control strategy relies on the decision making and cooperation of a number of intelligent software agents to control and coordinate various components on the shop floor. One of the most important agents for this control strategy is the product agent, which is the decision maker for a single part in the manufacturing system. To improve the flexibility and adaptability of the product agent and its control strategy, this work proposes a direct and active cooperation framework for the product agent. The directly and actively cooperating product agent can identify and actively negotiate scheduling constraints with other agents in the system. A new modeling formalism, based on priced timed automata, and an optimization-based decision making strategy are proposed as part of the framework. Two simulation case studies showcase how direct and active cooperation can be used to improve the flexibility and performance of manufacturing systems.


2021 ◽  
Author(s):  
Ilya Kovalenko ◽  
Efe Balta ◽  
Dawn Tilbury ◽  
Kira Barton

Due to the advancements in manufacturing system technology and the ever-increasing demand for personalized products, there is a growing desire to improve the flexibility of manufacturing systems. Multi-agent control is one strategy that has been proposed to address this challenge. The multi-agent control strategy relies on the decision making and cooperation of a number of intelligent software agents to control and coordinate various components on the shop floor. One of the most important agents for this control strategy is the product agent, which is the decision maker for a single part in the manufacturing system. To improve the flexibility and adaptability of the product agent and its control strategy, this work proposes a direct and active cooperation framework for the product agent. The directly and actively cooperating product agent can identify and actively negotiate scheduling constraints with other agents in the system. A new modeling formalism, based on priced timed automata, and an optimization-based decision making strategy are proposed as part of the framework. Two simulation case studies showcase how direct and active cooperation can be used to improve the flexibility and performance of manufacturing systems.


2014 ◽  
Vol 47 (3) ◽  
pp. 8503-8508 ◽  
Author(s):  
Abdelfetah HENTOUT ◽  
Mohamed Ayoub MESSOUS ◽  
Brahim BOUZOUIA

CAUCHY ◽  
2013 ◽  
Vol 2 (4) ◽  
pp. 189
Author(s):  
Sentot Achmadi ◽  
Miswanto Miswanto

This paper discuss multi-agent model of the N-dimensional space with the function of attraction and repulsion. In this model is given the disturbance function which is a bounded function. In this paper also discuss about stationary of each agency and stability of the models use stability of Lyapunov. From the analytical results obtained center of the multi-agent is stationary. Also test the stability with Lyapunov method is obtained that the proposed model is a stable model. Numerical simulation results show that each agent will converges to a region that has a certain distance to the center of the multi-agent model


2020 ◽  
Vol 28 (3) ◽  
pp. 109-121
Author(s):  
V.S. Bykova ◽  
◽  
L.A. Martynova ◽  
A.I. Mashoshin ◽  
I.V. Pashkevich ◽  
...  

Algorithms for a dispatcher of a multi-agent control system for an autonomous underwater vehicle (AUV) are described. The algorithms are designed on a modular basis, which provides for the control of a wide range of tasks assigned to the AUV, and, in addition, makes the implementation of each algorithm simple.


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