scholarly journals Multi-Agent Task Planning Based on Distributed Resource Scheduling under Command and Control Architecture

2019 ◽  
Author(s):  
Jie Zhang ◽  
Gang Wang ◽  
Yafei Song
Keyword(s):  
Resource Scheduling ◽  
Command And Control ◽  
Coordination Mechanism ◽  
Control Architecture ◽  
Planning Problem ◽  
Task Planning ◽  
Architecture Model ◽  
Multi Agent ◽  
And Control ◽  
Multi Agents

For the task planning problem of the command and control architecture, the existing algorithms have problems such as low efficiency and poor re-planning quality under abnormal conditions. Based on the requirements of the current accusation architecture, this paper constructs a distributed command and control architecture model based on multi-agents, which makes use of the superiority of multi-agents in dealing with complex tasks. The concept of MultiAgents-HTN is proposed under the framework. The original hierarchical task network planning algorithm is optimized, the multi-agent collaboration framework is redefined, and the coordination mechanism of local conflict is designed. Taking the classical resource scheduling problem as the experimental background, the comparison between the proposed algorithm and the classical HTN algorithm is carried out. The experimental results show that the proposed algorithm has higher quality and higher efficiency than the existing algorithm, and the space anomaly is heavy during processing. The planning is more efficient, and the time is more complicated and superior in dealing with the same problem, with good convergence and adaptability. The conclusion proves that the distributed command and control architecture proposed in this paper has high practicability in related fields and can solve the problem of distributed command and control architecture in multi-agent environment.

scholarly journals Multiagent Task Planning Based on Distributed Resource Scheduling under Command and Control Structure

2019 ◽  
Vol 2019 ◽  
pp. 1-14
Author(s):  
Jie Zhang ◽  
Gang Wang ◽  
Yafei Song ◽  
Fangzheng Zhao ◽  
Siyuan Wang
Keyword(s):  
Control Structure ◽  
Resource Scheduling ◽  
Command And Control ◽  
Coordination Mechanism ◽  
Task Planning ◽  
Good Convergence ◽  
Hierarchical Task Network ◽  
Planning Algorithm ◽  
Low Efficiency ◽  
And Control

For task planning of the command and control structure, the existing algorithms exhibit low efficiency and poor replanning quality under abnormal conditions. Given the requirements of the current accusation architecture, a distributed command and control structure model is built in this paper based on multiagents, which exploits the superiority of multiagents in achieving complex tasks. The concept of MultiAgent-HTN is proposed based on the framework. The original hierarchical task network planning algorithm is optimized, the multiagent collaboration framework is redefined, and the coordination mechanism of local conflict is developed. With the classical resource scheduling problem as the experimental background, the proposed algorithm compared with the classical HTN algorithm is drawn. According to the experimental results, the proposed algorithm exhibits higher quality and higher efficiency than the existing algorithm and the space anomaly is significant in the course of processing. The planning is more efficient and the time is more complicated and superior in solving the same problem, and the algorithm exhibits good convergence and adaptability. In the conclusion, it is proved that the distributed command and control structure proposed in this paper exhibits high practicability in relevant fields and can solve the problem of distributed command and control structure in a multiagent scenario.

Multi-Agent Control System for the Movement of Uniaxial Objects

2015 ◽  
Vol 237 ◽  
pp. 183-188
Author(s):  
Mirosław Mrozek
Keyword(s):  
Control System ◽  
Point Of View ◽  
Multi Agent Systems ◽  
Control Groups ◽  
Agent Systems ◽  
Multi Agent ◽  
Agent Control ◽  
Classical Control ◽  
And Control ◽  
Multi Agents

Multi-agent systems are used mainly in IT solutions and control groups of robots. From the point of view of classical control architectures, they are a kind of distributed systems in which nodes perform advanced algorithms, usually associated with the technology of artificial intelligence, and they can be considered as agents. The article describes the multi-agents control system of objects of uniaxial movements. An example of such a system to control a repository with movable racks with electric motors is presented. Each rack acts as an agent through the implemented control of the resources of embedded microcontrollers. Such a system provides high quality control, guaranteeing long-lasting, trouble-free operation while maintaining the safety of both service and stored items.

scholarly journals Multi-Agents Architecture for Scheduling and Control of Robotic Manufacturing Systems

2002 ◽  
Vol 7 (1) ◽  
pp. 177
Author(s):  
Brahim Bouzouia
Keyword(s):  
Flexible Manufacturing ◽  
Manufacturing Systems ◽  
Prototype System ◽  
Multi Agent Systems ◽  
Real Time Control ◽  
Distributed Intelligence ◽  
Time Control ◽  
Multi Agent ◽  
And Control ◽  
Multi Agents

This paper presents an  innovative Multi-Agent approach related to an advanced real time control  of flexible manufacturing systems. The proposed architecture is based on the paradigm of Distributed Intelligence and Multi-Agent Systems. The developed  Multi-Agent prototype system integrates  the following functions: Scheduling, dispatching, monitoring and error handling. A new negotiation protocol for manufacturing systems is presented in this paper. The purpose of this protocol is to assign dynamic operations to the resources of the Manufacturing System in order to accomplish the proposed tasks. This protocol is able to deal with exceptions.  

scholarly journals A Framework for Multi-Agent UAV Exploration and Target-Finding in GPS-Denied and Partially Observable Environments

Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4739
Author(s):  
Ory Walker ◽  
Fernando Vanegas ◽  
Felipe Gonzalez
Keyword(s):  
Remote Sensing ◽  
Reinforcement Learning ◽  
Search Problem ◽  
Planning Problem ◽  
Planning And Control ◽  
Points Of Interest ◽  
Multi Agent ◽  
The Individual ◽  
Partially Observable ◽  
And Control

The problem of multi-agent remote sensing for the purposes of finding survivors or surveying points of interest in GPS-denied and partially observable environments remains a challenge. This paper presents a framework for multi-agent target-finding using a combination of online POMDP based planning and Deep Reinforcement Learning based control. The framework is implemented considering planning and control as two separate problems. The planning problem is defined as a decentralised multi-agent graph search problem and is solved using a modern online POMDP solver. The control problem is defined as a local continuous-environment exploration problem and is solved using modern Deep Reinforcement Learning techniques. The proposed framework combines the solution to both of these problems and testing shows that it enables multiple agents to find a target within large, simulated test environments in the presence of unknown obstacles and obstructions. The proposed approach could also be extended or adapted to a number of time sensitive remote-sensing problems, from searching for multiple survivors during a disaster to surveying points of interest in a hazardous environment by adjusting the individual model definitions.

Multi-Agent Based Modeling of Warship Combat Command and Control System

2012 ◽  
Vol 246-247 ◽  
pp. 898-902
Author(s):  
Xing Zhong Wang
Keyword(s):  
Control System ◽  
Role Model ◽  
Heterogeneous Systems ◽  
Command And Control ◽  
Interaction Model ◽  
Design System ◽  
Model Interaction ◽  
Multi Agent ◽  
And Control ◽  
Command And Control System

To solving the inefficiency-problem in warship combat command and control system, this paper builds multi-agent oriented system architecture. It uses CORBA to support communication among heterogeneous systems and uses UML to design system prototype. Taking our two warships chasing an enemy-warship collaboratively for example, this paper illustrates the agent-oriented modeling process, including the role model, interaction model, state model and class model. This approach is able to meet the needs of modeling the warship combat command and control system.

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