UUV agent behavior learning and evolution model based on chaotic immune genetic mechanism

An immune genetic and evolutionary model technology, applied in the field of underwater unmanned system modeling and simulation, can solve the problem that the search efficiency and accuracy of the global search space need to be improved, etc.

Inactive Publication Date: 2019-12-27
SHAANXI NORMAL UNIV
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AI Technical Summary

Problems solved by technology

[0006] Although these immune algorithms can achieve problem solving, the search efficiency and accuracy in the global search space need to be improved

Method used

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  • UUV agent behavior learning and evolution model based on chaotic immune genetic mechanism
  • UUV agent behavior learning and evolution model based on chaotic immune genetic mechanism
  • UUV agent behavior learning and evolution model based on chaotic immune genetic mechanism

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Embodiment 1

[0069] In order to better understand the technical scheme of the present invention, the following more specific instructions are made:

[0070] Such as figure 1 , a UUV agent behavior learning and evolution model based on chaotic immune genetic mechanism, including the following steps:

[0071] Step 1: Antigen recognition: load the problem to be solved and constraints as the antigen Ag;

[0072] Taking the UUV to autonomously avoid underwater obstacles in the underwater space of 10000m×10000m as the solution problem, the combat environment, target state and its own state are taken as constraints to realize the display and expression of the antigen as Ag.

[0073] Step 2: Vaccine extraction: use experts and prior knowledge and use the characteristics of antigen Ag as vaccine information h j , which uses binary coding to form a genome, and the construction scale is N 1 Vaccine group AH:

[0074]

[0075] Where: T is the matrix transpose symbol;

[0076] Use experts and p...

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Abstract

The invention belongs to the technical field of underwater unmanned system modeling and simulation, and particularly relates to a UUV intelligent agent behavior learning and evolution model based on achaotic immune genetic mechanism. The method comprises the following steps: firstly, loading a to-be-solved problem and constraint conditions as antigen Ag, and generating an initialized antibody population according to a vaccine population, a memory population and a chaotic mechanism; secondly, controlling the convergence direction of the learning process by utilizing a vaccination mechanism according to an antibody fitness calculation result, and completing updating of an antibody memory bank; and finally, sequentially designing a selection operator based on roulette, a crossover operator based on adaptive adjustment and a mutation operator based on Gaussian and polynomial mixing to realize diversity of the antibody population, and performing premature suppression, thereby realizing updating and iteration of the antibody population. The model combines the advantages of the global search capability of a basic genetic algorithm and the local search capability of an immune and chaoticmechanism, and promotes the quick learning and evolution of behavior rules by continuously adjusting and optimizing the search space of a problem solution.

Description

technical field [0001] The invention belongs to the technical field of underwater unmanned system modeling and simulation, and in particular relates to a UUV intelligent body behavior learning and evolution model based on a chaotic immune genetic mechanism. Background technique [0002] Military UUV is a complex underwater unmanned combat system in which combat elements such as weapons and equipment, underwater environment, and combat missions are coupled and interact with each other. It has the characteristics of large endurance, good concealment, low risk, and recyclability. If the unmanned system plays an important role in combat missions such as search and reconnaissance, long-range attack, submarine defense, and networking detection, it must have strong intelligence, specifically manifested in the fact that UUV can complete functions such as detection, identification, and communication. And realize autonomous behavior response, planning and learning, to ensure high-qual...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N7/08G06N3/00G06F17/50
CPCG06N3/006G06N7/08
Inventor 梁洪涛高洁
Owner SHAANXI NORMAL UNIV
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