Intelligent group collaborative combat generation method based on self-learning algorithm

Abstract

The invention belongs to the technical field of cooperative combat methods, and particularly discloses an intelligent group cooperative tactical method generation method based on a self-learning algorithm, and the method comprises the following steps: S1, generating a plurality of group cooperative tactical meta actions according to a combat task; s2, abstracting a specific group algorithm of each group collaborative tactical meta action, wherein the specific group algorithm comprises the following steps: S2.1, generating problem modeling by an intelligent group collaborative tactical method; a distributed Markov decision-making process is used for modeling a group collaborative tactical method generation problem; s2.2, proposing a neural network model for solving the problem; s2.3, generating a self-learning algorithm by using a group collaborative combat method; and S3, by using a self-learning algorithm, the unmanned cluster generates a set of mutually cooperative intelligent group cooperative combat method according to the combat factors. The group cooperation tactical meta-action is a predefined logic behavior, logic functions related to a plurality of combat tasks are decomposed into small logic behaviors, operations which cannot be fused with each other in the execution control process are reduced, and the autonomy of the unmanned cluster is improved.

Description

technical field [0001] The invention belongs to the technical field of collaborative combat methods, and in particular relates to a method for generating an intelligent group collaborative combat method based on a self-learning algorithm. Background technique [0002] In the future, the form of warfare is always changing with the advancement of military technology, and the way of combat is developing rapidly in the direction of intelligence. With the development of artificial intelligence, multi-agent systems, coordination and control and other technologies, swarm cooperative operations emerge as the times require. The complex battlefield environment on the opposite side, the situation of our side and the situation of the enemy and other factors, the unmanned swarm is driven by the tasks of target recognition, intelligence analysis, auxiliary decision-making, and coordinated operations, and puts forward an urgent need for intelligent group combat algorithms. The research on...

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Problems solved by technology

[0004] The purpose of the present invention is to provide a method for generating intelligent group cooperative tactics based on a self-learning algorithm, so as to solve the problem that the current self-learning algorithm for intelligent group cooperative operations cannot realize the selection of the optimal strategy, resulting in that the combat method cannot be optimal and the combat Problems where the results do not meet expectations

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