Abstract
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.
Highlights
There are many methods for optimization of distributed programming, which are mainly divided into three types: numerical analysis method, heuristic algorithm, and hybrid algorithm
In order to overcome the drawbacks of heuristic algorithm, to deal with the problem of complex distributed programming constraint model and to find the best solution, a hybrid algorithm is proposed
A distributed command and control structure model based on multiagent is constructed to meet the demand of current command and control structure. e problem of large amount of data and complex situation environment of emergency events is solved using the high collaboration efficiency of multiagent and the superiority of solving complex problems
Summary
There are many methods for optimization of distributed programming, which are mainly divided into three types: numerical analysis method, heuristic algorithm, and hybrid algorithm. For the complicated distributed resource planning problem, it is impossible to obtain the satisfactory optimal solution by using only the numerical analysis method. For the particularity of the emergency response, the accusation architecture is characterized by large scale, hierarchical decision-making, complex cooperative relationship, and robust spatio-temporal constraint as well as complex external situation [5]. Under complex requirements for solution, i.e., input complex tasks, the task is decomposed layer by layer, several simple tasks are decomposed, and the task is processed according to the concept of multiagent system Following this principle, the decision-making process requires certain empirical knowledge and rules [7]. Conventional mathematical modelling is not suitable for solving such problems for its slow solution speed, complex cooperative relationship, and spatio-temporal state constraints. Targeted optimization is conducted in this paper based on the HTN to solve the decision-making generation problem of distributed accusation architecture. Heuristic searches select appropriate operators or methods based on their ranks
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