An Inversion Identification Method for Cooperative Strategy of Multi-agent System

Abstract

The invention discloses an inversion identification method of a cooperative strategy of a multi-agent system. By adopting a linear quadratic optimal control method, a multi-agent system cooperative strategy inversion identification model is constructed based on the dynamic characteristics of an agent, which can The collaborative strategy is calculated based on the discrete state observations in the limited time domain. At the same time, the inversion identification model established by the present invention can simultaneously estimate the real motion state of the agent, thus realizing accurate collaborative strategy inversion under noise interference.

Description

technical field [0001] The invention belongs to the technical field of system identification and parameters, and in particular relates to an inversion identification method of a multi-agent system coordination strategy. Background technique [0002] The inverse problem refers to determining the parameters (or model parameters) that characterize the problem based on the results and some general principles (or models). In engineering applications, inversion problems widely appear in the fields of geophysics, biology, medicine and construction. Inversion refers to the artificial intelligence system that can imitate the computer program system of human intelligence, which has the functions of learning and reasoning. Such as expert systems, artificial neural network systems, etc. In the process of solving inverse problems, artificial intelligence methods and technologies are used to guide local or global optimization. This inversion method is called artificial intelligence inve...

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Problems solved by technology

However, in practical applications, the inversion modeling task must be completed within a limited time sequence. This method cannot be realized, and this algorithm first identifies the optimal feedback gain matrix and then calculates the corresponding objective function parameter matrix, which involves a large number of parameter calculations. The computing platform is difficult to realize and practically use

[0005] There are still two difficulties in applying the above-mentioned optimal inversion modeling method to the identification of multi-agent system cooperative strategies: one is to combine the characteristics of multi-agent cooperative systems, properly describe the problem, and establish a concise and practical multi-agent system. On the other hand, for the case of discrete finite time domain, it is difficult for the above method to carry out accurate and reliable inversion identification of the cooperative strategy of multi-agent system under the influence of noise

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